Copyright TechTarget - All rights reserved https://cyber.law.harvard.edu/rss/rss.html Techtarget Feed Generator en Sun, 26 Apr 2026 03:18:16 GMT https://www.techtarget.com/searcherp editor@techtarget.com <p>Hybrid work is not defined by where employees sit. It is an operating model decision about how work gets done, who owns it and what happens when it breaks. Most organizations make the first call deliberately; many never make the other two. As a result, accountability for success -- or failure -- is still a mystery at many companies.</p> <p>"The most common breakdown I see in distributed engineering organizations isn't missing ownership; <a href="https://www.techtarget.com/searchunifiedcommunications/feature/Patterns-forming-in-enterprise-software-ownership">it's ambiguous ownership</a>. Two people think they own something. Neither is wrong based on what was communicated. The gap usually lies between how leadership assigned work and how the systems recorded it," said Sayali Patil, a former AI product manager at Splunk.</p> <p>While the situation is untenable, it is understandable. The systems are <a href="https://www.techtarget.com/searchenterpriseai/tip/How-agentic-RAG-supports-effective-business-workflows">designed to connect workflows</a>, not assign ownership of them. The CRM, ERP, collaboration tools and other software that enterprises rely on span business units, geographies and organizational boundaries by design. But connectivity is not accountability. And in a hybrid operating model, the difference between those two things is where risk accumulates, where audit trails go thin and where the question of who owns the outcome stops having a clean answer.</p> <p>"Platforms like CRM and ERP are increasingly used to track task assignments, but they often capture only committed states of work. They are used as infrastructure debt where the human effectively becomes the API between disconnected systems," said Manish Garg, co-founder, chief product officer and COO at Skan.ai, a process intelligence platform.</p> <p>"While they strengthen tracking, system-enforced workflows can introduce rigidity by failing to account for the 70%-80% of 'happy path' variations. This leads to 'checkbox ownership' where the logged steps are followed, but the underlying decision logic remains ungoverned and invisible," Garg explained.</p> <section class="section main-article-chapter" data-menu-title="Signs of trouble"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Signs of trouble</h2> <p>The typical hybrid enterprise operates with distributed teams, multi-cloud infrastructure and cross-enterprise applications threading CRM, ERP and collaboration platforms across business units and geographies. Accountability in this complex setup does not fail all at once; it erodes incrementally, hand-off by hand-off, time zone by time zone, system by system.</p> <p>The signs are everywhere. It can look like a customer escalation that lives in Salesforce but requires action in SAP; a compliance obligation that spans a regional HR platform and a global procurement workflow; or a collaboration tool that captures the decision but not the owner. No single failure is catastrophic. Early intervention does not happen.&nbsp;&nbsp;</p> <p>By the time leadership sees the pattern, the damage has already been baked into operations, vendor contracts, org design and the gap between what the enterprise believes it controls and what it actually does.</p> <p>"Activity metrics are a trap in hybrid environments. A person can generate high Slack volume, attend every standup and do none of the work that actually matters. The shift to outcome-based measurement requires leaders to define success criteria at the point of assignment -- not after the fact," said Patil.</p> </section> <section class="section main-article-chapter" data-menu-title="The visibility paradox"> <h2 class="section-title"><i class="icon" data-icon="1"></i>The visibility paradox</h2> <p>"Hybrid work did not create an accountability crisis. It exposed how much accountability previously depended on proximity," said Ben Perreau, CEO of Parafoil, a leadership intelligence tool provider.</p> <p>Perreau said that in office environments, managers relied on "ambient signals" such as noting who was in the room, who spoke up and who visibly followed through on the deliverables. "Those signals were never reliable, but they gave leaders a felt sense of control. Distributed work stripped that away, and most organizations replaced it with nothing," he said.</p> <blockquote class="main-article-pullquote"> <div class="main-article-pullquote-inner"> <figure> Hybrid work did not create an accountability crisis. It exposed how much accountability previously depended on proximity. </figure> <figcaption> <strong>Ben Perreau </strong>CEO of Parafoil </figcaption> <i class="icon" data-icon="z"></i> </div> </blockquote> <p>The systems that exist do appear to surface work in accountable ways. Visibility and verifiability -- two keys to accountability -- seem to be achieved. But that usually is not the case. This creates the visibility paradox: the appearance of visibility where none or little actually exists.</p> <p>"The accountability gap I see most consistently in hybrid environments isn't about effort; it's about undocumented decisions at handoff points," said Steve Rosas, principal at Omega Environmental Services.</p> <p>Rosas said that in environmental remediation, for example, when a field technician flags an anomaly and the project manager is remote, "that finding can get buried in a Slack thread instead of the project record."</p> <p>Herein lie two problems: scattered key data points and a focus on only what these systems can detect.</p> <p>"Digital trails in systems like Jira or CRMs influence perceptions of accountability, but they only capture what the system logged, not what the person actually did," said Garg.</p> <p>"These trails miss the 'connective tissue,' meaning the manual work not logged in core systems of record, across unstructured systems like Outlook, Excel, Slack, Adobe, Notepads, etc.," Garg added.</p> <p>The bottom line: Much of the real work is not noted in any of the systems. It is almost impossible to discern who gets credit for the work being done or who gets the blame.</p> <p>"Leaders need to actively audit this. In my experience on global engineering teams, the highest-impact contributors are frequently the least visible, and performance systems that optimize for activity signals will consistently misattribute ownership and credit," said Patil.</p> </section> <section class="section main-article-chapter" data-menu-title="Making ownership real"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Making ownership real</h2> <p>The issue of ownership -- that is, the bearer of responsibility, authority and accountability -- should not be determined after the fact when people are seeking to assign blame or steal credit. Instead, it should be one of the first issues addressed on any project, regardless of size.</p> <p>That assertion appears simple and obvious at first take. But that is not how the real world works.</p> <p>"Decision rights in most hybrid enterprises are underdefined at the edges, not at the center. The CEO knows what they own. The ambiguity lives at the cross-functional layer: Where does product end and engineering begin? Where does customer success hand off to support?" said Patil.</p> <p>"Distributed work absolutely increases escalation loops because the informal resolution mechanisms that used to exist -- a quick conversation in a hallway, a real-time calibration -- are gone. The structural fix is to define decision rights at the handoff points explicitly, before a conflict surfaces, not as a response to one," Patil added.</p> <p>A key thing to understand is that CRM, ERP and collaboration platforms are "increasingly doing what management used to do, which is <a href="https://www.techtarget.com/searcherp/feature/Enterprise-platforms-are-evolving-piece-by-piece">enforcing workflow, assigning ownership and creating audit trails</a>," said Patil. That's largely positive, she says, but the risk is in checkbox ownership rather than in true accountability designations.</p> <p>The next important point to wrap your head around is the nature of the accountability problem.</p> <p>The most common executive misunderstanding, according to Patil, is that accountability is a cultural problem. "It isn't -- or rather, it isn't <i>only</i> cultural. Accountability breaks down in hybrid environments primarily because the systems and structures that used to enforce it passively no longer exist. That's an organizational design problem. Culture follows structure, not the other way around," Patil explained.</p> <p>So, what might the fix for that look like? Perreau recommends assigning explicit decision owners to every cross-functional initiative, not just to project managers. The distinction matters, he says, since project managers coordinate and decision owners are <a href="https://www.techtarget.com/searcherp/feature/10-early-decisions-that-shape-enterprise-software-outcomes">accountable for outcomes</a>.</p> <p>"Most hybrid accountability breakdowns trace back to a missing decision owner, someone with the authority and responsibility to make the call and answer for the result. When nobody owns the decision, everybody owns the process, and that is where accountability quietly disappears," Perreau added.</p> <p><i>Pam Baker is a freelance journalist and the author of books including </i>ChatGPT for Dummies<i> and </i>Generative AI for Dummies<i>. Baker is also an instructor on AI topics for LinkedIn Learning and a member of the National Press Club, the Society of Professional Journalists and the Internet Press Guild.</i></p> </section> Hybrid operating models reveal hidden accountability gaps across enterprise systems. Learn how leaders define decision rights, assign ownership and improve auditability. https://cdn.ttgtmedia.com/visuals/ComputerWeekly/Hero%20Images/internet-of-things-IoT-network-fotolia.jpg https://www.techtarget.com/searcherp/feature/Who-owns-the-outcome-Accountability-in-the-hybrid-enterprise Mon, 20 Apr 2026 09:44:00 GMT <p><iframe title="Career cure for AI phobia: Be a beekeeper, not a worker bee" allowtransparency="true" height="150" width="100%" style="border: none; min-width: min(100%, 430px); height: 150px;" scrolling="no" data-name="pb-iframe-player" src="https://www.podbean.com/player-v2/?i=htafv-1a9ffb0-pb&amp;from=pb6admin&amp;pbad=0&amp;share=1&amp;download=1&amp;rtl=0&amp;fonts=Arial&amp;skin=1&amp;font-color=auto&amp;logo_link=episode_page&amp;btn-skin=2baf9e" loading="lazy"></iframe></p> <p>It's now abundantly clear that AI is more likely to transform most jobs than it is to eliminate jobs entirely. AI seems here to stay, and employers increasingly mandate its use or strongly encourage it in the way that Don Corleone made "an offer he can’t refuse" in <i>The Godfather</i>.</p> <p>That means it's probably time for workers to jettison principled resistance and <a href="https://www.techtarget.com/searchenterpriseai/feature/How-to-start-a-career-in-AI-Advice-from-experts">learn to use AI to their individual advantage</a>, but in ways that don't conflict with the goals of their organization.</p> <p>In this episode of <i>Enterprise Apps Unpacked, </i>speaker and author Sharon Gai gives advice on doing just that. <a target="_blank" href="https://www.amazon.com/How-More-Less-Future-Proofing-AI-driven/dp/1394352360" rel="noopener">Her new book</a>, <i>How to Do More with Less: Future-Proofing Yourself in an AI-driven Economy</i>, came out on March 31.</p> <div class="imagecaption alignRight"> <img src="https://cdn.ttgtmedia.com/rms/onlineimages/gai_sharon.jpg " alt="Sharon Gai, speaker and author">Sharon Gai </div> <section class="section main-article-chapter" data-menu-title="To bee or not to bee? That is the question"> <h2 class="section-title"><i class="icon" data-icon="1"></i>To bee or not to bee? That is the question</h2> <p>A frequent keynote speaker on AI, e-commerce and digital transformation, Gai has appeared in major media, such as ABC, CNN and Bloomberg, and consulted for brands including Intel. For four years until 2022, she worked at Chinese e-commerce and AI giant Alibaba, advising brands on their digital marketing strategies.</p> <p>The book is replete with stories from her days in China, including the night when Alibaba engineers excitedly demoed a technological breakthrough: <a href="https://www.techtarget.com/searchenterpriseai/definition/generative-AI">generative AI</a> continuously spewing out designs for the website banners, photos and text used in marketing campaigns -- even calculating likely conversion rates for different options, a process that took humans thousands of hours. Gai wondered if the AI would replace her and decided the solution was learning how to do more with less.</p> <p>Gai began this podcast by explaining both sides of that equation: what AI enables people to do more of, and what they can do less of by handing it over to AI.</p> <p>"The big concept in the book -- and why there's a bee on the cover -- is, pre-2022, we were looking at work like busy bees and were all very, very busy. It was endless to-dos, endless projects, things to go through," she said. "Post-2022, we can be beekeepers, where we're overseeing, where we create the environment for things to run in."</p> <p>Gai offered reassurance to people worried about job loss with seemingly counterintuitive advice: Go as far as you can to replace yourself before your CEO does. It starts with writing down every task that your job comprises. The list is likely to have 20 to 30 tasks -- more if the job is complicated.</p> <p>Next, lump together tasks that are clearly within AI's capabilities. "You'll realize that's maybe 30% or 50% of your job," Gai said. "In a very scary scenario, if that's 70%-80% of your job, you should have alarm bells going off. But then you will notice there are also tasks that are very, very human, or it will always need <i>you</i>. After you are very clear on what part of your job is quite outsourceable or AI can do already, start to find the right workflows, AI agents, AI systems, skills -- <a href="https://www.techtarget.com/searchsoftwarequality/tip/How-to-choose-the-best-Markdown-editor-for-your-use-case">Markdown files</a>, even -- that can do those tasks and start to replace yourself with it."</p> <p>As AI evolves and roles change, people need to stay aware of the parts of their jobs that are "AI-able" and those that aren't and continue to improve their skills in the latter, she said. "The better muscles you build there, the more future-proof you can be, so that however better AI becomes next year and the year after that, there is a layer of your job that is hard to let go of."</p> <p>Other topics discussed in the podcast include the following:</p> <ul class="default-list"> <li>Common characteristics of tasks that can be automated versus requiring human creativity and judgment.</li> <li>How managers can use AI to help with their strategic and supervisory responsibilities.</li> <li>Who is responsible for upskilling employees and whether employees can do it on their own.</li> <li>Whether standards and technology are far enough along to support the beekeeper model of agentic AI deployment.</li> </ul> <p><i>David Essex is an industry editor who creates in-depth content on enterprise applications, emerging technology and market trends for several Informa TechTarget websites.</i></p> </section> In this podcast, author Sharon Gai shares advice from her new book on using AI to do more with less and future-proof your job by building the innately human skills that will last. https://cdn.ttgtmedia.com/visuals/digdeeper/1.jpg https://www.techtarget.com/searcherp/podcast/Career-cure-for-AI-phobia-Be-a-beekeeper-not-a-worker-bee Mon, 20 Apr 2026 05:00:00 GMT <p><a href="https://www.techtarget.com/searchenterpriseai/definition/agentic-AI"><i>Agentic AI</i></a><i> deployments in businesses so far have been reminiscent of the "rogue IT" days of SaaS, with employees accessing or demanding unauthorized apps, authorized tools just starting to roll out, and business and IT leaders scrambling to articulate a coherent strategy for the organization.</i></p> <p><i>True, sanctioned pilots are plentiful, but many organizations report frustration with scaling up these agentic AI applications, in part because the apps are designed to handle narrow tasks. Security, governance and data foundations are usually works in progress, and </i><a href="https://www.techtarget.com/searcherp/podcast/Plan-a-multi-agent-orchestration-framework-for-scalable-AI"><i>multi-agent orchestration</i></a><i> -- getting agents to collaborate on complex tasks and goals -- remains unsolved for in-house developers and software vendors.</i></p> <p><i>Deloitte, the Big Four accounting firm and IT consultancy, has been introducing advisory services and online tools designed to help clients draft and execute agentic AI roadmaps that produce tangible business results.</i></p> <p><i>In this Q&amp;A, China Widener, Deloitte's vice chair and U.S. technology, media and telecommunications industry leader, explained how to escape "pilot purgatory" and plot a strategy for scalable agentic AI. She also shared advice on addressing </i><a href="https://www.techtarget.com/searchcio/feature/AI-job-losses-Transformation-expected-not-mass-layoffs"><i>AI job loss fears</i></a><i> by redesigning work in ways that benefit both individuals and their organizations.</i></p> <p><i>Widener is approaching her 20th anniversary at Deloitte in May. She previously held C-suite roles in Ohio state government and was an assistant county prosecutor.</i></p> <p><i>Editor's note: This interview was edited for clarity and brevity.</i></p> <p><b>If you could name one thing, what's preventing companies from going beyond pilots and getting enterprise-wide ROI from agentic AI?</b></p> <div class="imagecaption alignLeft"> <img src="https://cdn.ttgtmedia.com/rms/onlineimages/widener_china.jpg" alt="China Widener, Deloitte Vice Chair and U.S. Technology, Media &amp; Telecommunications Industry Leader">China Widener </div> <p><b>China Widener:</b> It is more than one thing, without question, but central to all the things is this idea of clarity around the vision. There's now, there's next, and there's the future, and each one wrought value. The question is, what are you starting with?</p> <p>This is not a technology problem -- the tech works. The question is in what context and to what end, which is about the vision the organization has for itself.</p> <p>You can extract value in the form of cost containment or mitigation and create value through growth, new products, tools and services or a change of experiences. Where you start your journey is a function of understanding what your goals are. What you identify then becomes the set of questions.</p> <p>More than half of companies in our survey are early stage or don't have a strategy. That's a challenge because you don't have a roadmap for where you are going or a way to judge the progress you're making, let alone the steps to take.</p> <p><b>Deloitte's 2026 "State of AI in the Enterprise" survey </b><a target="_blank" href="https://www.deloitte.com/us/en/what-we-do/capabilities/applied-artificial-intelligence/content/state-of-ai-in-the-enterprise.html" rel="noopener"><b>captured insights</b></a><b> from more than 3,200 business and IT leaders directly involved in AI initiatives. Only a third said they used AI to truly transform their business. The report suggested that's because most are still focused on training employees for AI fluency and haven't done enough to redesign work. Why is redesigning work so important?</b></p> <p><b>Widener:</b> There's value that simply comes from doing a task faster. The notion of <a href="https://www.techtarget.com/searchenterpriseai/feature/AI-upskilling-strategies-that-center-workers-not-tech">upskilling and getting people AI fluent</a> is to get them hands on -- to touch AI, work with it and utilize it when executing their daily duties. Nothing about their job has changed; it's just whether they can do it faster, more efficiently or with more precision.</p> <p>There's a step in the process that asks how to use AI to augment an employee's cognitive skill set. Research shows the greatest lift is leveling up employees to create a certain level of cognitive parity. But if you just apply it to the work they already do, you make what they do efficient but haven't asked whether they need to do it anymore.</p> <p>Redesigning work allows you to change the way time is spent and on what. Today, a function may have 17 tasks associated with it. If we redesign the work itself, there may only be 10 tasks in the future because some of them can be executed through some form of automation. You've freed up significant time and can give that same person different or additional work. They can focus on the 10 tasks that you can't automate or shouldn't automate and really require human judgment.</p> <p><b>Many workers are worried about losing their jobs or jobs changing so much that they can't keep up. How should organizations handle training and upskilling so employees trust they'll get help moving into new roles?</b></p> <p><b>Widener:</b> It's like most things. There's an evolutionary path of travel. You don't wake up on Tuesday and suddenly have adopted and adapted to the technological change. You start to make things available to employees so they can take the work they already know how to do but augment it and do it faster -- a research job, for example. Ultimately, the research can happen in a more comprehensive, quicker way. The product you produce, which is still your product, is produced with greater quality and more robustness because you've had access to those tools.</p> <p>Then there's moving the individual forward to cognitive enhancement or support of their thought process and giving them access to tools for that. It's this stepping approach that moves employees forward to having an agent that will execute some of the most repeatable functions. But where judgment and quality are required, the human takes on managing the agent.</p> <blockquote class="main-article-pullquote"> <div class="main-article-pullquote-inner"> <figure> This is not a technology problem -- the tech works. The question is in what context and to what end. </figure> <figcaption> <strong>China Widener</strong>Vice chair, Deloitte </figcaption> <i class="icon" data-icon="z"></i> </div> </blockquote> <p>You have to step a workforce through that. It's not just training. Some organizations approach it as just needing to upskill people. Upskilling is important but it's not the whole story.</p> <p>There's also a <a href="https://www.techtarget.com/searchenterpriseai/tip/Get-AI-change-management-right-A-checklist-for-success">change management aspect</a>. Our research has shown that some things are underrated by leaders in organizations -- things like redesigning roles. AI fluency matters, and it enables adoption and execution -- hard measurables, such as how much time was saved and what degree of revenue was generated. Those things are tangible and easily calculable.</p> <p>The intangibles, though, are equally important, and that's the change management function: how you are thinking about the operating model of the organization when you have this technological capability available to you.</p> <p><b>What agentic AI use cases are you seeing in the industries in your purview?</b></p> <p><b>Widener:</b> We were just having this conversation about agentic AI and its capacity to be creative and create efficiency, productivity and effectiveness. It begs a natural question for any organization, whether you are growing, concerned about being disintermediated or looking for your next corporate strategy to <a href="https://www.techtarget.com/searchcio/feature/Agentic-ai-in-practice-lessons-from-real-deployments">take full advantage of agentification</a> and the opportunities it creates.</p> <p>Agentification isn't impacting every industry in exactly the same way. In some industries, it looks more internally focused and efficiency-driven and changes back-office functionality. For others, such as the entertainment industry, there is impact to the core of the business, the creativity of storytelling. It has a different impact in that industry vs. hardware, where it may be about changing the management of a supply chain.</p> <p><b>What are clients' most frustrating challenges in taking agentic AI beyond the pilot stage and getting enterprise-wide use from it?</b></p> <p><b>Widener:</b> That <i>is</i> the biggest pain point. Most companies have done some form of experimentation or pilot. Some think of it as pilot purgatory because the percentage of pilots they've been able to take to scale has been less than 20%. The value proposition of agentification isn't in question. What <i>is</i> in question is how to reap the value and benefit from it faster and at scale.</p> <p>The challenges that have arisen start with the pilot itself and whether it has been constructed to solve an enterprise problem versus solving a particular productivity problem in isolation for a few or one specific use case. But is that use case one that should be scaled, and is it scalable?</p> <p>Technological and <a href="https://www.techtarget.com/searchdatamanagement/tip/Experts-share-practices-to-overcome-AI-data-readiness">data choices</a> get made in pilots that don't scale later. The pilot can't be framed against a narrow use case. It has to be framed against the broader infrastructure, understanding the bigger data questions that might arise and recognizing that governance will be significant. A data-quality question in a pilot might be manageable because the pilot is small but no longer manageable when you scale. You have to decide the scale questions as part of the pilot, not build the pilot and say you'll worry about scale questions later.</p> <p><b>What should companies put in place to approach agentic AI from a scalability viewpoint and execute on that level?</b></p> <p><b>Widener:</b> Pilots tend to grow in a fairly organic way: Organizations buy access to a particular <a href="https://www.techtarget.com/whatis/definition/large-language-model-LLM">LLM</a> or AI tool and unleash it on the body as a whole and let people who do a job use the tools to improve something. Then they harvest the best of those ideas and look at whether they should be scaled.</p> <p>There are organizations that have instead taken a broader, top-down or enterprise approach and said, "These are the tool sets we want to utilize, and here's where we want to focus them."</p> <p>What's critical in all this, no matter which end of the spectrum you start from, is having a disciplined approach to agentifying any aspect of the business. It doesn't matter who the stakeholder is. If you have a consistent and disciplined approach by which ideas are evaluated and their proposed value is calculated, and you understand the technical implications, then you can get to real consistency.</p> <p>No organization agentifies overnight. Every organization starts in some way -- maybe by capability, maybe by business unit. But if you don't have a consistent and disciplined evaluative process, everybody starts in a different place, calculates a different benefit and executes against a different vision.</p> <p>A disciplined approach requires a few components. One is clarity on how you'll choose goals. Is it about cost? Growth? Experience? You have to be clear because there are things that are a better fit for agentification that may bring middle value. Some things may bring higher value, but the fit's going to be a heavier lift.</p> <p>You also need standards and protocols to evaluate those things to arrive at the right place for your agentification bet, based first and foremost on what you value, and then moving the organization on a periodic basis through the same evaluation to arrive at a focus. You'll get consistency and clarity and understand what you're spending money on, what value to expect in return and be able to calculate and monitor that value.</p> <p><b>Agentic AI is trendy, but it's happening in a broader context that includes </b><a href="https://www.techtarget.com/searchenterpriseai/definition/generative-AI"><b>generative AI</b></a><b> and large language models, some of which are older. What are the foundational elements of agentic AI that business and IT leaders should focus on first?</b></p> <p><b>Widener:</b> The more autonomy you want your agents to have, the more important your governance and data quality are, because an autonomous agent is going to work independently. It's not going to seek permission to execute. And the more autonomy you create, the greater the security that is necessary. They are important at the start because they become even more important as you reach more and more autonomy.</p> <p><b>Deloitte introduced a tool called Enterprise AI Navigator. What is it, and how do people get it?</b></p> <p><b>Widener:</b> It was created because there wasn't a consistent tool out there that allowed organizations to have the kind of disciplined approach that is applicable in the moment and in the future.</p> <p>It is not something we sell to clients as a product but the tool we use to help clients move through their agentic journey and arrive at both their roadmap and the outcomes they have identified. It allows you to have greater confidence in the choices you've made.</p> <p>Your future workflow -- the change to the work itself that we talked about -- is proposed so you see it before the first agent is coded. You understand what your future is going to look like and can start to understand how your operating model changes and the changes you need to make to the workforce in terms of training, upskilling or job shift. You know all of that going in.</p> <p>Today, those are things discovered along the way, and that's what contributes to pilot purgatory. You need to know them when you start your agentic journey, not when you're already in it.</p> <p><i>David Essex is an industry editor who creates in-depth content on enterprise applications, emerging technology and market trends for several Informa TechTarget websites.</i></p> Deloitte exec says redesigning work is key and explains how to do it without stoking job-loss fears -- but only after a rigorous goal-setting process that sets clear priorities. https://cdn.ttgtmedia.com/rms/onlineimages/ai_a199952058.jpg https://www.techtarget.com/searcherp/news/366641954/How-to-escape-agentification-pilot-purgatory-for-scalable-AI Fri, 17 Apr 2026 14:19:00 GMT <p>AI might earn trust first not in the flashiest corners of enterprise software, but in some of the most structured ones. Transactional work gives AI something a lot of other enterprise tasks do not: narrower use cases, repeatable steps, clearer rules and outcomes that are easier to measure.</p> <p>If companies are looking for places where AI can start to earn trust, procurement, sourcing, manufacturing and other structured workflows look like some of the strongest candidates.</p> <section class="section main-article-chapter" data-menu-title="Transactional work gives AI clearer boundaries"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Transactional work gives AI clearer boundaries</h2> <p>Oracle's latest push helps explain why. Its new agentic applications are being positioned not around one giant agent trying to do everything, but around teams of <a href="https://www.techtarget.com/searcherp/news/366640636/Oracle-calls-Fusion-Agentic-Applications-next-level-AI-for-ERP">agents working together toward business objectives</a>.</p> <p>Big outcomes are made up of smaller outcomes. That helps explain why transactional work matters here.</p> <p>Procurement, sourcing and manufacturing are all large ERP domains made up of smaller, more repeatable tasks. They are the kinds of workflows where it is easier to imagine AI taking on narrow responsibilities without immediately asking organizations to trust it with the whole process.</p> <p>Oracle's human-in-the-loop and human-in-the-lead model also feels more grounded in this context. In transactional work, the path from full oversight to partial autonomy is easier to picture because the rules are clearer and success is easier to define. In that setting, AI in ERP feels less like a moonshot and more like a controlled attempt to expand trust over time.</p> <p>What still feels unresolved is how vendors or customers actually decide when the system has performed well enough to deserve more independence.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/procure_to_pay_process-f.png "> <img data-src="https://www.techtarget.com/rms/onlineimages/procure_to_pay_process-f_mobile.png " class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/procure_to_pay_process-f_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/procure_to_pay_process-f.png 1280w" alt="Graphic showing the steps in the procure-to-pay process, including purchase request, vendor selection, requisition, purchase order, order confirmation, receipt of order, invoice reconciliation and accounts payable." height="206" width="559"> <figcaption> <i class="icon pictures" data-icon="z"></i>Procure-to-pay is the kind of structured, repeatable workflow where enterprise AI might be able to prove value early because the steps, handoffs and outcomes are easier to define and measure. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> </section> <section class="section main-article-chapter" data-menu-title="Procurement makes AI case more concrete"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Procurement makes AI case more concrete</h2> <p>Procurement makes the case more concrete because it is one of the clearest places where AI can prove its value right now. Spend visibility, continuous risk monitoring, accounts payable and supply-chain resilience are all <a href="https://www.techtarget.com/searcherp/tip/4-benefits-of-implementing-automation-in-procurement">narrow enough to be believable</a> and important enough to matter.</p> <p>The value is also easier for executives to see. Better visibility into spend, fewer payment errors, faster responses to disruption and more proactive risk monitoring all translate into outcomes that are operationally and financially legible. In that sense, procurement feels like one of the clearest places where AI can show what it is good at without requiring companies to buy into a much broader transformation story all at once.</p> <p>Procurement is also a reminder not to oversell the technology. Automation works best when the underlying data is clean and when the workflows make sense. That gets at the real limit of the transactional proving-ground idea.</p> <blockquote class="main-article-pullquote"> <div class="main-article-pullquote-inner"> <figure> AI does not rescue a bad process simply by being layered on top of it. </figure> <i class="icon" data-icon="z"></i> </div> </blockquote> <p>AI does not rescue a bad process simply by being layered on top of it. If the workflow is dysfunctional or the data is weak, automation can just scale the dysfunction.</p> <p>Organizational readiness matters especially here.</p> <div class="extra-info"> <div class="extra-info-inner"> <p></p> <h3 class="splash-heading">Where transactional friction still hides</h3> <p>Some of the clearest opportunities for transactional AI still come from very old problems. In <a href="https://www.techtarget.com/searcherp/podcast/Direct-materials-sourcing-technology-a-hub-for-manufacturers">direct materials sourcing</a>, for example, fragmented bills of materials, disconnected supplier workflows and manual coordination between engineering, procurement, suppliers, finance and manufacturing can slow product development and cut into margins. Narrower automation and AI use cases can start to show value in these environments, where the workflow gaps are often visible, expensive and repetitive enough that improvement can be measured. When AI is introduced, the question is simply whether the technology can reduce wasted motion, accelerate decisions and improve resilience without introducing new process problems.</p> </div> </div> </section> <section class="section main-article-chapter" data-menu-title="Manufacturing strengthens the AI use case"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Manufacturing strengthens the AI use case</h2> <p>Manufacturing pushes the same argument from a different angle. The strongest use cases are not broad claims that AI is reinventing the factory. Instead, they are practical uses tied to forecasting, documentation, computer-aided design, inventory and purchasing decisions, predictive maintenance, and coding assistance in more digitally mature environments.</p> <p>The strongest projects share a few traits: clear operational or financial outcomes, high-quality and structured data, defined human oversight, and realistic deployment inside existing workflows. Those are the conditions that make <a href="https://www.techtarget.com/searcherp/feature/10-AI-use-cases-in-manufacturing">AI in manufacturing</a> feel practical rather than speculative.</p> <p>The caution is part of why the manufacturing case feels more grounded. Generative AI is still not suitable for many mission-critical use cases, and many of the most realistic applications are still in the back office or in tightly bounded operational settings with human oversight. That limitation also keeps the use case from being oversold.</p> <p>If AI is going to earn wider trust in manufacturing, it will likely do so first through pragmatic, time-saving applications that fit into existing processes rather than through sweeping promises of autonomy.</p> </section> <section class="section main-article-chapter" data-menu-title="Sourcing points in the same direction"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Sourcing points in the same direction</h2> <p>Direct materials sourcing has long been slowed by fragmented bills of materials, disconnected supplier workflows and manual coordination gaps between engineering, procurement, suppliers, finance and manufacturing. That kind of friction is exactly the sort of environment where narrower AI and automation use cases can start to prove value -- not by replacing the whole process at once, but by making a stubborn, expensive, highly transactional part of it move faster and with less waste.</p> <p>Taken together, transactional work looks like one of the strongest early tests for enterprise AI. It is not that these areas are simple; it is that they are well-defined enough to let AI work within clearer boundaries. That gives companies a better shot at measuring results, defining oversight and deciding where more autonomy is justified.</p> <p><i>James Alan Miller is a veteran technology editor and writer who leads Informa TechTarget's Enterprise Software group. He oversees coverage of ERP &amp; Supply Chain, HR Software, Customer Experience, Communications &amp; Collaboration and End-User Computing topics.</i></p> </section> AI might initially earn trust in transactional work, where narrower tasks, cleaner data and clearer oversight make procurement and manufacturing stronger proving grounds. https://cdn.ttgtmedia.com/rms/onlineimages/iot_g1212287865.jpg https://www.techtarget.com/searcherp/feature/AI-could-earn-trust-in-transactional-work-first Wed, 15 Apr 2026 15:08:00 GMT <p>The global digital transformation <a href="https://www.grandviewresearch.com/industry-analysis/digital-transformation-market" target="_blank" rel="noopener">market</a> is forecast to grow more than fourfold, from $1.07 trillion in 2024 to $4.62 trillion by 2030. These numbers show that organizations recognize the value of <a href="https://www.techtarget.com/searchcio/definition/digital-transformation">digital transformation</a> in today's fast-moving, technology-driven business landscape.</p> <p>Firms that prioritize digital transformation rely on many technologies to modernize their legacy systems and processes. Modernization enables them to be more efficient, relevant, resilient and responsive; to continuously innovate; and to remain competitive -- even amid market changes and environmental disruptions. In short, digital transformation is a critical factor that differentiates successful companies from the also-rans.</p> <p>Undoubtedly, <a href="https://www.techtarget.com/searchcio/tip/Top-10-digital-transformation-benefits-for-business">digital transformation can yield numerous business benefits</a>. However, not all transformation initiatives are successful. In fact, only 30% of companies successfully <a href="https://www.bcg.com/capabilities/digital-technology-data/digital-transformation/overview" target="_blank" rel="noopener">navigate</a> such initiatives, according to the Boston Consulting Group. One reason for the high failure rate is that many firms pursue transformation at breakneck speeds but fail to prioritize governance discipline. Prioritizing unrestrained experimentation and rapid modernization without governance controls can create a host of issues and hinder them from achieving their transformation goals.</p> <p>To avoid these problems, companies need to temper transformation speed with strong governance. This means ensuring that elements like clear decision rights, platform ownership, data governance policies, architecture standards and cross-functional accountability structures are in place <i>before</i> the transformation initiative takes off.</p> <p>This article examines the factors driving organizations' interest in digital transformation, the role of enterprise platforms in enabling transformation and -- most importantly -- why <a href="https://www.techtarget.com/searchdatamanagement/feature/Good-governance-key-to-reducing-high-AI-project-failure-rate">enterprise governance is critical</a> to its success.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/cio-tips_for_successful_dx-f.png "> <img data-src="https://www.techtarget.com/rms/onlineimages/cio-tips_for_successful_dx-f_mobile.png " class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/cio-tips_for_successful_dx-f_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/cio-tips_for_successful_dx-f.png 1280w" alt="Visual list of key steps involved in making digital transformation a success" height="303" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>Successful digital transformation (DX) requires more than just new technology. Careful planning, collaboration, monitoring, training, testing and developing recovery procedures in case of system failure or breach are all necessary components. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <section class="section main-article-chapter" data-menu-title="Factors driving the need for digital transformation"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Factors driving the need for digital transformation</h2> <p>Digital transformation is a deliberate and strategic initiative aimed at transforming business operations, processes, culture, supply chains, customer interactions and even employees' skill sets. By deploying the right technologies at scale, organizations can improve operational efficiency, optimize costs and unlock new revenue streams. They can also improve customer experience (<a href="https://www.techtarget.com/searchcustomerexperience/definition/customer-experience-CX">CX</a>), accelerate innovation, respond more quickly to market changes and evolving customer demands, and build a stronger competitive advantage in a fast-evolving market economy. All these potential benefits drive organizations' need to accelerate digital transformation initiatives.</p> <p>Many other factors also pressure firms to move quickly on such initiatives:</p> <ul class="default-list"> <li><b>Competitive pressures and industry-wide digitization.</b> When competitors adopt advanced technologies and digital-first operational models to change how they operate and deliver value, organizations are forced to accelerate transformation -- or risk losing customers and market share.</li> <li><b>Pressure from the business ecosystem.</b> Third-party entities like partners, suppliers and vendors that are already digitized can influence organizations to upgrade their own systems to ensure compatibility, ease collaboration and capture powerful synergies.</li> <li><b>Technological advancements. </b>Cutting-edge technologies like generative AI, machine learning and <a href="https://www.techtarget.com/searchbusinessanalytics/feature/6-big-data-benefits-for-businesses">big data analytics</a> can improve operational agility, enhance decision-making and accelerate business innovation -- potential benefits that might compel firms to adopt these technologies in a hurry to stay competitive.</li> <li><b>Evolving customer expectations.</b> The increasing demand for seamless, personalized and digital-first CX from customers pushes companies to quickly embrace tech-driven process and product modernization.</li> <li><b>Executive mandates.</b> Strong "top-down" executive directives and priorities drive new initiatives to modernize legacy systems across the enterprise.</li> <li><b>Regulatory changes.</b> Some national laws and industry-specific regulations mandate specific digital systems and controls to avoid fines and legal troubles, pushing organizations to prioritize fast digital transformation.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="Enterprise platforms as transformation enablers"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Enterprise platforms as transformation enablers</h2> <p>Enterprise platforms like <a href="https://www.techtarget.com/searcherp/definition/ERP-enterprise-resource-planning">ERP</a>, <a href="https://www.techtarget.com/whatis/video/An-explanation-of-customer-relationship-management-CRM">CRM</a>, HR, workflow automation and supply chain systems influence the direction, pace, scale and ultimate success of any digital transformation strategy and initiative. These and other business-critical systems provide a strong foundation for firms to integrate and coordinate core business processes, workflows and data. Well-designed, properly configured and customized systems based on the latest technologies enable organizations to improve operational efficiency, augment the capabilities of human workers, eliminate communication silos and make better, data-driven decisions.</p> <p>Transformation initiatives interact with these platforms at many touchpoints, such as during legacy platform modernization or when migrating on-premises workloads to the cloud. Firms might adopt new platforms when redesigning business processes or streamlining core business functions. Cutting-edge software can also aid efforts to digitize CX, capture real-time data insights or improve supply chain visibility.</p> <div class="youtube-iframe-container"> <iframe id="ytplayer-0" src="https://www.youtube.com/embed/gdVyxURWBRc?autoplay=0&amp;modestbranding=1&amp;rel=0&amp;widget_referrer=null&amp;enablejsapi=1&amp;origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0"></iframe> </div> </section> <section class="section main-article-chapter" data-menu-title="The risks of weak governance"> <h2 class="section-title"><i class="icon" data-icon="1"></i>The risks of weak governance</h2> <p>Regardless of which platform they implement, organizations could face numerous problems if their governance structure does not support the digital transformation strategy. Fast-paced initiatives lacking clear governance can lead to the following unintended consequences:</p> <ul class="default-list"> <li>System fragmentation or redundancy.</li> <li>Increased <a href="https://www.techtarget.com/whatis/definition/technical-debt">technical debt</a>.</li> <li>Inconsistent data models.</li> <li>Operational instability, leading to customer and employee dissatisfaction as well as <a href="https://www.techtarget.com/searchdatabackup/feature/The-cost-of-downtime-and-how-businesses-can-avoid-it">increased downtime</a>.</li> <li>Cost escalation.</li> <li>Increased <a href="https://www.techtarget.com/searcherp/tip/Learn-benefits-and-challenges-of-CRM-and-ERP-integration">integration complexity</a>.</li> <li>Inflated security and compliance risk.</li> </ul> <p>These financial and operational consequences could linger for the long term, even if the modernization effort appears successful in the short term.</p> <blockquote class="main-article-pullquote"> <div class="main-article-pullquote-inner"> <figure> The key to successful and long-term digital transformation is controlled momentum rather than unrestricted acceleration. </figure> <i class="icon" data-icon="z"></i> </div> </blockquote> <p>The key to successful and long-term digital transformation is <i>controlled</i> <i>momentum</i> rather than <i>unrestricted acceleration</i>. And to achieve this momentum, a strong governance framework is essential. Such a framework can support the modernization initiative without destabilizing core operations, creating fragmented technology environments and causing security or compliance gaps.</p> </section> <section class="section main-article-chapter" data-menu-title="Key governance structures that sustain momentum"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Key governance structures that sustain momentum</h2> <p>Organizations that achieve successful digital transformation balance speed and control during the effort because they have <a href="https://www.techtarget.com/searcherp/feature/How-governance-maturity-affects-MA-integration-outcomes">mature governance structures</a>. A multi-layered governance framework should incorporate multiple elements, including the following:</p> <ul class="default-list"> <li>Clearly defined decision rights for business and technology leaders.</li> <li>Enterprise architecture standards guiding modernization initiatives and ensuring that the initiatives align with long-term business goals.</li> <li><a href="https://www.techtarget.com/searchdatamanagement/feature/Data-and-AI-governance-must-team-up-for-AI-to-succeed">Cross-functional governance groups</a> strategizing, reviewing and signing off on transformation initiatives.</li> <li>Data governance policies that ease data lifecycle management and maintain data consistency, quality and integrity across systems.</li> <li>Access and identity management controls with clearly defined access levels and privileges to ensure safe and authorized access to systems and data.</li> <li><a href="https://www.techtarget.com/searchhrsoftware/tip/4-benefits-of-HR-following-change-management-practices">Change management controls</a> to facilitate stable and seamless system changes with minimal disruptions.</li> <li>Incident management mechanisms to identify and mitigate risks or issues during and after implementation.</li> <li>Regular compliance audits to maintain consistent adherence to relevant standards and regulatory requirements.</li> <li>Clearly defined <a href="https://www.techtarget.com/searchenterpriseai/tip/Top-AI-KPIs-that-business-leaders-need-to-know">metrics and KPIs</a> to monitor system performance and track implementation success.</li> <li>Documentation controls to maintain consistent documentation and version control across systems and teams.</li> </ul> <p>A popular misconception is that these mechanisms hinder transformation and decelerate results. On the contrary, they act as guardrails and catalysts that speed up transformation initiatives. A mature governance structure allows for continual experimentation and "<a href="https://www.techtarget.com/whatis/definition/fail-fast">fail fast</a>" modernization, and it maintains accountability and integration across enterprise platforms. It also prevents potential long-term structural problems that typically arise from transformation efforts, such as operational instability, integration complexity, and <a href="https://www.techtarget.com/searchcio/feature/What-the-Global-Risks-Report-means-for-CIOs">rising operational costs and risks</a>.</p> </section> <section class="section main-article-chapter" data-menu-title="Why digital transformation is ultimately a leadership balancing act"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Why digital transformation is ultimately a leadership balancing act</h2> <p>Ultimately, any digital transformation initiative is an ongoing balancing act that leaders need to undertake. To execute the digital transformation strategy and realize its stated objectives, leaders must balance speed with control. A strong governance ecosystem can help them maintain this balance.</p> <p>With the right governance measures in place, leaders can determine where and when experimentation should occur and who is authorized to approve major platform changes. Time-tested governance controls also ease decisions regarding which initiatives should be standardized across the enterprise, how data should be managed and secured, and which technologies and systems are most likely to serve business goals.</p> <p>The bottom line? In the long term, successful transformation depends on whether leaders have implemented a sturdy, multi-layered governance structure -- and whether this structure can support the transformation initiative's momentum and goals.</p> <p><i>Rahul Awati is a PMP-certified project manager with IT infrastructure experience spanning storage, compute and enterprise networking.</i></p> </section> The success of digital transformation hinges on balancing rapid innovation with strong governance to avoid risks like fragmentation, technical debt and operational instability. https://cdn.ttgtmedia.com/rms/onlineimages/competition_g1220259544.jpg https://www.techtarget.com/searcherp/feature/Digital-transformation-Balancing-speed-and-governance Fri, 10 Apr 2026 09:00:00 GMT <p>Agents are easy to announce. Orchestration is harder to prove.</p> <p>Shipping agents is one thing. Making them work together across systems, handoffs and live operating environments without creating more risk, duplication or confusion is something else entirely.</p> <p>That is where the next enterprise AI test is starting to take shape. The issue is no longer just whether vendors can build agents. It is whether those agents can operate across real workflows, follow common rules and hold together in the mixed environments most enterprises actually run.</p> <section class="section main-article-chapter" data-menu-title="Orchestration starts to look like architecture"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Orchestration starts to look like architecture</h2> <p>AI orchestration is starting to look less like a feature and more like an architectural control layer.</p> <p>As <a href="https://www.techtarget.com/searcherp/podcast/Plan-a-multi-agent-orchestration-framework-for-scalable-AI">multi-agent systems spread across workflows,</a> applications and even corporate firewalls, scale quickly becomes more than a model problem. Once that happens, security, compliance and performance consistency can no longer live within each agent. They must hold together across the environment those agents move through.</p> <p>That is why the idea of a policy-enforcement layer matters. It offers a way to apply business rules and compliance requirements across agents and workflows without rebuilding the same control logic repeatedly. It also hints at a deeper shift in enterprise software itself.</p> <p>If agents are going to operate at scale, applications might increasingly have to be built less around screen-by-screen user journeys and more around modular services, APIs and workflows that agents can call as easily as people can use them.</p> <div class="extra-info"> <div class="extra-info-inner"> <h3 class="splash-heading">What orchestration must do now</h3> <p>Orchestration is starting to matter because it sits where several enterprise requirements intersect. It must help agents follow common rules, move across workflows, hand off to humans cleanly and operate inside live systems without creating more inconsistency. That makes it less of a narrow AI capability and more of a control layer that touches policy, operations and software design all at once.</p> <p>Seen that way, orchestration is not just about agent-to-agent communication. It is about holding together the larger environment those agents move through: applications, workflows, permissions, compliance requirements and human decision points.</p> <p>That is why the term keeps widening. It has to.</p> </div> </div> </section> <section class="section main-article-chapter" data-menu-title="Salesforce spells out the operating layer"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Salesforce spells out the operating layer</h2> <p>Salesforce keeps returning to the same operating language: <a href="https://www.techtarget.com/searchcustomerexperience/news/366640897/Salesforce-Agentforce-head-discusses-future-of-AI-agents">context, control, observability and orchestration</a>. That is a more practical way to frame the problem than simply saying enterprises need better AI governance. It suggests that the real challenge starts after the agent is built, when it must run in a live environment, follow a structured process and avoid breaking down under more complex instructions.</p> <p>Salesforce's language also broadens what orchestration actually means. It is not just about agents managing other agents. It is about agents coordinating with human processes and handoffs across systems like Slack, HR, IT and accounting. That is a useful distinction.</p> <p>Building agents is a narrow end in itself. Running an agentic enterprise is broader. It depends on how agents, applications and people interact across the stack, not just on what any single model can do in isolation.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/comparing_automation_and_orchestration_how_they_work-f.png "> <img data-src="https://www.techtarget.com/rms/onlineimages/comparing_automation_and_orchestration_how_they_work-f_mobile.png " class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/comparing_automation_and_orchestration_how_they_work-f_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/comparing_automation_and_orchestration_how_they_work-f.png 1280w" alt="Chart comparing automation and orchestration across goals, scope, intervention, compatibility, customization and human involvement." height="380" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>This comparison helps explain why orchestration is becoming a bigger enterprise AI issue than automation alone: It coordinates complex workflows, dependencies and cross-system execution. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> </section> <section class="section main-article-chapter" data-menu-title="Orchestration gets real in the contact center"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Orchestration gets real in the contact center</h2> <p>Orchestration gets easier to picture in the contact center. Bringing <a href="https://www.techtarget.com/searchcustomerexperience/news/366639947/Agentforce-Contact-Center-brings-native-CCaaS-to-Salesforce">voice, automation, CRM data, AI agents and digital channels</a> into a single system shows where orchestration starts to matter in practical terms: cross-channel context, automated resolution, human escalation and cleaner handoffs inside a real operating environment.</p> <p>It also makes the point in a realistic way: this is not really a rip-and-replace story. Organizations can layer the platform alongside existing contact center environments and see which parts of the broader vision can actually be lit up.</p> <p>That is probably closer to how orchestration will play out across enterprise software more broadly. It will not arrive in perfect greenfield conditions. It will have to prove itself inside existing, layered, often messy environments.</p> </section> <section class="section main-article-chapter" data-menu-title="The buyer problem is now universal"> <h2 class="section-title"><i class="icon" data-icon="1"></i>The buyer problem is now universal</h2> <p>More broadly, orchestration is not just a vendor-positioning issue. Buyers are already dealing with AI overload, agent sprawl and single-source-of-truth <a href="https://www.techtarget.com/searchunifiedcommunications/feature/Enterprise-Connect-2026-brings-AI-from-hype-to-reality">questions in multi-vendor shops.</a> They are also trying to figure out how to link different AIs together, reduce redundancy and turn all the AI talk into practical business value. That makes orchestration a present-tense enterprise problem, not a future one.</p> <p>That could be the most important shift of all.</p> <blockquote class="main-article-pullquote"> <div class="main-article-pullquote-inner"> <figure> Building agents is a narrow end in itself. Running an agentic enterprise is broader. </figure> <i class="icon" data-icon="z"></i> </div> </blockquote> <p>The real buyer problem might not be choosing one AI tool. It could be figuring out how to make the multiple AI tools already chosen by the enterprise -- or chosen for it by the software vendors it uses -- work together without creating more fragmentation.</p> <p>In that sense, orchestration is less a story about individual products than a story about a universal enterprise problem now surfacing across the stack.</p> </section> <section class="section main-article-chapter" data-menu-title="The real differentiator"> <h2 class="section-title"><i class="icon" data-icon="1"></i>The real differentiator</h2> <p>That is why orchestration is becoming the make-or-break layer.</p> <p>Vendors are getting better at shipping agents. The harder challenge now is making those agents, systems and workflows work together in a way enterprises can actually trust.</p> <p>Can agents follow the rules? Can they move across systems cleanly? Can they hand off to humans at the right point? Can they operate in live environments without multiplying risk or confusion? Those are no longer side questions. They are fast becoming the main event.</p> <p><i>James Alan Miller is a veteran technology editor and writer who leads Informa TechTarget's Enterprise Software group. He oversees coverage of ERP &amp; Supply Chain, HR Software, Customer Experience, Communications &amp; Collaboration and End-User Computing topics.</i></p> </section> Vendors can ship agents. The harder challenge is orchestrating how they work across applications, workflows and human handoffs without creating more risk. https://cdn.ttgtmedia.com/rms/onlineimages/strategy_a296343799.jpg https://www.techtarget.com/searcherp/feature/Orchestration-is-becoming-enterprise-AIs-real-test Thu, 09 Apr 2026 09:00:00 GMT <div> <div> <p paraeid="{2b55f4a4-8b26-4838-9c6c-5eeeb4c36567}{116}" paraid="30752366"><span xml:lang="EN-US" data-contrast="auto">It's&nbsp;commonplace for M&amp;A deals to be evaluated based on projections around valuation,&nbsp;synergy&nbsp;and strategic&nbsp;fit. Before a deal goes through, M&amp;A experts carefully analyze&nbsp;a target&nbsp;company's current value. They also&nbsp;attempt&nbsp;to draw a picture of its future financial health, explore opportunities for generating synergies, and examine critical aspects like cultural compatibility, legal&nbsp;liabilities&nbsp;and&nbsp;deal&nbsp;alignment with long-term business goals.</span><span data-ccp-props="{&quot;201341983&quot;:0,&quot;335559740&quot;:312}">&nbsp;</span></p> </div> <div> <p paraeid="{2b55f4a4-8b26-4838-9c6c-5eeeb4c36567}{130}" paraid="1825093359"><span xml:lang="EN-US" data-contrast="auto">These careful&nbsp;</span><em><span xml:lang="EN-US" data-contrast="auto">pre-deal</span></em><span xml:lang="EN-US" data-contrast="auto">&nbsp;assessments are crucial for M&amp;A success.</span><span data-ccp-props="{&quot;201341983&quot;:0,&quot;335559740&quot;:312}">&nbsp;</span></p> </div> <div> <p paraeid="{2b55f4a4-8b26-4838-9c6c-5eeeb4c36567}{140}" paraid="1797183686"><span xml:lang="EN-US" data-contrast="auto">However, it is the&nbsp;</span><em><span xml:lang="EN-US" data-contrast="auto">post-deal</span></em><span xml:lang="EN-US" data-contrast="auto">&nbsp;integration phase that&nbsp;ultimately determines&nbsp;whether the deal's projected value materializes. And during this phase,&nbsp;</span><em><span xml:lang="EN-US" data-contrast="auto">governance maturity</span></em><span xml:lang="EN-US" data-contrast="auto">&nbsp;is vital. This&nbsp;concept&nbsp;refers to the presence of clear decision rights and escalation paths, well-established platform&nbsp;ownership&nbsp;and cross-functional accountability structures, along with&nbsp;</span><a rel="noreferrer noopener" target="_blank" href="https://www.techtarget.com/searchdatabackup/tip/Enterprise-data-governance-Frameworks-and-best-practices"><span xml:lang="EN-US" data-contrast="none">effective data governance</span></a><span xml:lang="EN-US" data-contrast="auto">&nbsp;policies, architecture standards and risk management&nbsp;and&nbsp;compliance controls.</span><span data-ccp-props="{&quot;201341983&quot;:0,&quot;335559740&quot;:312}">&nbsp;</span></p> </div> <div> <p paraeid="{2b55f4a4-8b26-4838-9c6c-5eeeb4c36567}{172}" paraid="426708661"><span xml:lang="EN-US" data-contrast="auto">This article explores how governance structures can influence the success of M&amp;A integration,</span><span xml:lang="EN-US" data-contrast="none">&nbsp;</span><span xml:lang="EN-US" data-contrast="auto">particularly in enterprises that rely on complex digital platforms and systems.</span><span data-ccp-props="{&quot;201341983&quot;:0,&quot;335559740&quot;:312}">&nbsp;</span></p> </div> <div> <h2>Post-merger integration as a governance 'stress test'</h2> </div> <div> <p paraeid="{2b55f4a4-8b26-4838-9c6c-5eeeb4c36567}{188}" paraid="1216059574"><span xml:lang="EN-US" data-contrast="auto">During post-merger integration,&nbsp;</span><em><span xml:lang="EN-US" data-contrast="auto">on-paper</span></em><span xml:lang="EN-US" data-contrast="auto">&nbsp;M&amp;A strategy meets&nbsp;</span><em><span xml:lang="EN-US" data-contrast="auto">real-world</span></em><span xml:lang="EN-US" data-contrast="auto">&nbsp;execution. In this crucial phase, the stakes are high and the pressure to succeed is intense. Clarity,&nbsp;control&nbsp;and coordination are needed to withstand the pressure, successfully execute the&nbsp;initiative&nbsp;and achieve an&nbsp;M&amp;A's strategic objectives.&nbsp;Here's&nbsp;where a</span><span xml:lang="EN-US" data-contrast="none">&nbsp;</span><span xml:lang="EN-US" data-contrast="auto">strong governance framework plays a critical role. In fact, experts like Jake Henry, senior partner and co-leader of Mergers and Acquisitions at global management consultancy McKinsey &amp; Company,&nbsp;</span><a rel="noreferrer noopener" target="_blank" href="https://www.mckinsey.com/capabilities/m-and-a/our-insights/time-to-revisit-your-m-and-a-strategy"><span xml:lang="EN-US" data-contrast="none">directly link</span></a><span xml:lang="EN-US" data-contrast="auto">&nbsp;organizations' governance&nbsp;maturity&nbsp;and their leaders' governance&nbsp;proficiency&nbsp;with the ability of an M&amp;A deal to create value during integration.</span><span data-ccp-props="{&quot;201341983&quot;:0,&quot;335559740&quot;:312}">&nbsp;</span></p> </div> <div> <p paraeid="{2b55f4a4-8b26-4838-9c6c-5eeeb4c36567}{218}" paraid="1218334762"><span xml:lang="EN-US" data-contrast="auto">Organizations with mature governance structures tend to have the following:</span><span data-ccp-props="{&quot;201341983&quot;:0,&quot;335559740&quot;:312}">&nbsp;</span></p> </div> <div> <ul class="default-list"> <li>Well-defined enterprise-wide architecture standards.</li> <li>Clear system ownership and strong accountability.</li> <li>Unambiguous decision rights and authority.</li> <li>Explicit reporting lines and escalation paths.</li> <li>Established data governance frameworks.</li> <li>Systematic framework and controls for proactive risk management and compliance.</li> <li>Codified institutional knowledge through systematized, documented, repeatable processes.</li> <li>Cross-functional, data-driven decision-making.</li> <li>Transparent, timely, accurate flows of information and communications.</li> </ul> </div> </div> <div> <div> <p paraeid="{2374f242-2ad7-4c57-847b-34dace8b49d0}{23}" paraid="767455644"><span xml:lang="EN-US" data-contrast="auto">These firms can effectively and smoothly integrate systems, teams, processes, data&nbsp;models&nbsp;and decision authority across two companies. Leaders take more informed decisions and effectively manage common risks</span><span xml:lang="EN-US" data-contrast="none">&nbsp;</span><span xml:lang="EN-US" data-contrast="auto">during high-stakes post-merger integration,&nbsp;transformation&nbsp;and scaling. They can also reduce uncertainty and measure the outcomes of the deal&nbsp;across real teams,&nbsp;systems&nbsp;and decisions.</span><span data-ccp-props="{&quot;201341983&quot;:0,&quot;335559740&quot;:312}">&nbsp;</span></p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/data_governance_for_all_seasons_and_reasons-f.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/data_governance_for_all_seasons_and_reasons-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/data_governance_for_all_seasons_and_reasons-f_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/data_governance_for_all_seasons_and_reasons-f.png 1280w" alt="List of recommendations for creating a successful data governance program" height="420" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>Collaboration, continuous monitoring and training are all necessary components of successful governance frameworks. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> </div> <div> <p paraeid="{2374f242-2ad7-4c57-847b-34dace8b49d0}{43}" paraid="2115585423"><span xml:lang="EN-US" data-contrast="auto">Without a strong governance framework, gaps quickly&nbsp;emerge&nbsp;in decision-making, accountability, cross-functional coordination, compliance, risk&nbsp;oversight&nbsp;and business integration. These gaps could lead to unexpected integration delays or duplicated technology investments.</span><span data-ccp-props="{&quot;201341983&quot;:0,&quot;335559740&quot;:312}">&nbsp;</span></p> </div> <div> <p paraeid="{2374f242-2ad7-4c57-847b-34dace8b49d0}{49}" paraid="713982368"><span xml:lang="EN-US" data-contrast="auto">They also create&nbsp;</span><a rel="noreferrer noopener" target="_blank" href="https://www.techtarget.com/searchcio/tip/14-tips-for-CIOs-managing-shadow-IT-activities"><span xml:lang="EN-US" data-contrast="none">shadow IT that affects the firm's cybersecurity posture</span></a><span xml:lang="EN-US" data-contrast="auto">, along with data siloes that affect cross-functional collaboration and communication. Most importantly, weak governance hinders organizations from realizing critical&nbsp;synergies&nbsp;and achieving their strategic&nbsp;objectives.</span><span data-ccp-props="{&quot;201341983&quot;:0,&quot;335559740&quot;:312}">&nbsp;</span></p> </div> <div> <h2 paraeid="{2374f242-2ad7-4c57-847b-34dace8b49d0}{67}" paraid="940550291" aria-level="2" role="heading">Why governance maturity becomes critical after the deal closes</h2> </div> <div> <p paraeid="{2374f242-2ad7-4c57-847b-34dace8b49d0}{73}" paraid="1271059427"><span xml:lang="EN-US" data-contrast="auto">Whether an organization has a strong and mature governance structure becomes clear during post-merger integration. This period often exposes governance weaknesses that were previously manageable within a single organization but that now hinder M&amp;A integration and create a host of problems, including system incompatibility, operational disruptions, cross-functional data siloes, new cybersecurity vulnerabilities and higher technical debt.</span><span data-ccp-props="{&quot;201341983&quot;:0,&quot;335559740&quot;:312}">&nbsp;</span></p> </div> <div> <p paraeid="{2374f242-2ad7-4c57-847b-34dace8b49d0}{83}" paraid="206013966"><span xml:lang="EN-US" data-contrast="auto">To avoid these issues, leadership teams must address&nbsp;numerous&nbsp;high-priority issues, including the following:</span><span data-ccp-props="{&quot;201341983&quot;:0,&quot;335559740&quot;:312}">&nbsp;</span></p> </div> <div> <ul class="default-list"> <li>Which systems should survive.</li> <li>Who has authority to standardize platforms.</li> <li>Who owns integration decisions.</li> <li>How data should be reconciled across platforms.</li> <li>Which data model becomes canonical.</li> <li>How to resolve data ownership disputes.</li> <li>Who is responsible for risk and compliance management.</li> <li>How responsibilities should be divided across the combined organization.</li> <li>How cultural conflicts in tool usage will be addressed.</li> <li>How risk and compliance will be tracked.</li> <li>How technology investments will be tracked, and how their ROI will be assessed.</li> </ul> </div> </div> <div> <div> <p paraeid="{2374f242-2ad7-4c57-847b-34dace8b49d0}{155}" paraid="1936600416"><span xml:lang="EN-US" data-contrast="auto">Organizations with mature governance frameworks usually resolve these issues faster. They face few, if any, problems&nbsp;integrating platforms,&nbsp;processes&nbsp;and teams;&nbsp;aligning data models; and&nbsp;</span><a rel="noreferrer noopener" target="_blank" href="https://www.techtarget.com/searchsecurity/tip/How-to-implement-security-control-rationalization"><span xml:lang="EN-US" data-contrast="none">rationalizing technology portfolios</span></a><span xml:lang="EN-US" data-contrast="none">&nbsp;</span><span xml:lang="EN-US" data-contrast="auto">across the combined organization. In contrast, organizations with fragmented governance experience slower integration and increased operational complexity -- both undesirable consequences of ambitious M&amp;A deals.</span><span data-ccp-props="{&quot;201341983&quot;:0,&quot;335559740&quot;:312}">&nbsp;</span></p> </div> <div> <p paraeid="{2374f242-2ad7-4c57-847b-34dace8b49d0}{175}" paraid="1691330923"><span xml:lang="EN-US" data-contrast="auto">These issues explain why many M&amp;A experts and practitioners emphasize the importance of mature, strong governance in successful M&amp;A integration. One of them is Jonathan Milde, managing director and partner at Boston Consulting Group. Milde also recommends that organizations establish "</span><a rel="noreferrer noopener" target="_blank" href="https://www.bcg.com/publications/2024/technologys-role-in-the-post-merger-process"><span xml:lang="EN-US" data-contrast="none">steering mechanisms</span></a><span xml:lang="EN-US" data-contrast="auto">" and dedicated teams to coordinate all tech-related dependencies and, more importantly, to ensure that the "available technology supports the combined entity's business vision."</span><span data-ccp-props="{&quot;201341983&quot;:0,&quot;335559740&quot;:312}">&nbsp;</span></p> </div> <div> <h2>Enterprise platforms as the integration battleground</h2> </div> <div> <p paraeid="{2374f242-2ad7-4c57-847b-34dace8b49d0}{207}" paraid="1329511819"><span xml:lang="EN-US" data-contrast="auto">Technology is a key enabler of business operations,&nbsp;efficiency&nbsp;and productivity in modern organizations. Companies in every industry make use of advanced technologies through a variety of enterprise platforms, including ERP, CRM, workflow automation, supply chain and procurement, HR, workforce management, collaboration, data management and&nbsp;</span><a rel="noreferrer noopener" target="_blank" href="https://www.techtarget.com/searchbusinessanalytics/tip/Keys-to-building-a-successful-business-intelligence-team"><span xml:lang="EN-US" data-contrast="none">business intelligence systems</span></a><span xml:lang="EN-US" data-contrast="auto">.</span><span data-ccp-props="{&quot;201341983&quot;:0,&quot;335559740&quot;:312}">&nbsp;</span></p> </div> <div> <p paraeid="{2374f242-2ad7-4c57-847b-34dace8b49d0}{221}" paraid="888822089"><span xml:lang="EN-US" data-contrast="auto">These systems help to streamline operations, support data-driven decision-making,&nbsp;facilitate&nbsp;connectivity and collaboration, and drive business scalability and innovation. They deliver these benefits by encoding business processes and operational logic, which is why they often become the focal point of integration decisions&nbsp;after&nbsp;mergers or acquisitions.</span><span data-ccp-props="{&quot;201341983&quot;:0,&quot;335559740&quot;:312}">&nbsp;</span></p> </div> <div> <p paraeid="{2374f242-2ad7-4c57-847b-34dace8b49d0}{231}" paraid="54529166"><span xml:lang="EN-US" data-contrast="auto">Following M&amp;A deals, it can be challenging to integrate incompatible IT systems and&nbsp;consolidate&nbsp;disparate data, while also&nbsp;maintaining&nbsp;operational continuity and mitigating security risks. A mature, time-tested, multi-layered governance framework can help ease these challenges, influencing and simplifying multiple integration efforts, including the following:</span><span data-ccp-props="{&quot;201341983&quot;:0,&quot;335559740&quot;:312}">&nbsp;</span></p> </div> <div> <ul class="default-list"> <li>Platform consolidation, scaling, upgrades, modernization or decommissioning decisions.</li> <li><a href="https://www.techtarget.com/searchsecurity/tip/Cybersecurity-in-MA-due-diligence-Best-practices-for-executives">Cybersecurity management and protocols</a>.</li> <li>Data migration, integration and harmonization across systems.</li> <li>Identity and access management for users of the merged entity.</li> <li>Process standardization across organizations.</li> <li><a href="https://www.techtarget.com/searchcio/feature/Key-technical-debt-reduction-strategies">Addressing technical debt</a> due to IT overlaps or redundant applications.</li> </ul> </div> <div> <p paraeid="{29035921-10c4-461c-a7eb-d583e3d07ce5}{30}" paraid="447367278"><span xml:lang="EN-US" data-contrast="auto">Strong governance provides visibility into the tech stack, enabling organizations to select, manage and seamlessly harmonize technologies and systems, while lowering the risk of operational disruptions, lost productivity, communication&nbsp;breakdowns&nbsp;and innovation slowdowns.&nbsp;Ultimately, it&nbsp;ensures smooth post-merger integration and accelerates</span><span xml:lang="EN-US" data-contrast="none">&nbsp;</span><span xml:lang="EN-US" data-contrast="auto">synergy&nbsp;realization for all involved organizations.</span><span data-ccp-props="{&quot;201341983&quot;:0,&quot;335559740&quot;:312}">&nbsp;</span></p> </div> <div> <h2 paraeid="{29035921-10c4-461c-a7eb-d583e3d07ce5}{40}" paraid="296311446" aria-level="2" role="heading">Why governance ultimately shapes M&amp;A integration outcomes</h2> </div> <div> <p paraeid="{29035921-10c4-461c-a7eb-d583e3d07ce5}{46}" paraid="688189422"><span xml:lang="EN-US" data-contrast="auto">In 2025, global M&amp;A value&nbsp;</span><a rel="noreferrer noopener" target="_blank" href="https://www.mofo.com/resources/insights/260115-m-a-in-2025-and-trends-for-2026"><span xml:lang="EN-US" data-contrast="none">rose</span></a><span xml:lang="EN-US" data-contrast="auto">&nbsp;to a staggering&nbsp;$4.8 trillion, making it the second-highest M&amp;A value year on record.</span><span xml:lang="EN-US" data-contrast="none">&nbsp;</span><span xml:lang="EN-US" data-contrast="auto">Deal sizes also increased,</span><span xml:lang="EN-US" data-contrast="none">&nbsp;</span><span xml:lang="EN-US" data-contrast="auto">with a&nbsp;</span><a rel="noreferrer noopener" target="_blank" href="https://www.mckinsey.com/capabilities/m-and-a/our-insights/top-m-and-a-trends"><span xml:lang="EN-US" data-contrast="none"><span data-ccp-charstyle="Hyperlink">record-breaking</span></span></a><span xml:lang="EN-US" data-contrast="auto">&nbsp;60 M&amp;A deals&nbsp;valued&nbsp;at&nbsp;$10 billion&nbsp;or more&nbsp;completed last year. This cresting wave of M&amp;A activity is expected to continue&nbsp;in the near future, and experts predict that the same factors that drove M&amp;A activity in 2025 -- the availability of capital and financing options, a growing IPO market and a shifting regulatory environment -- will also fuel M&amp;A deals in 2026. These recent increases in dealmaking momentum are driven by organizations' recognition that M&amp;As are a critical business growth engine in today's hyper-competitive global economy.</span><span data-ccp-props="{&quot;201341983&quot;:0,&quot;335559740&quot;:312}">&nbsp;</span></p> </div> <div> <p paraeid="{29035921-10c4-461c-a7eb-d583e3d07ce5}{90}" paraid="1031095096"><span xml:lang="EN-US" data-contrast="auto">But growing optimism for M&amp;As</span><span xml:lang="EN-US" data-contrast="auto">&nbsp;</span><span xml:lang="EN-US" data-contrast="auto">notwithstanding, the risk of M&amp;A integration failure also&nbsp;remains&nbsp;very high. Over the past four decades, the M&amp;A failure rate has&nbsp;</span><a rel="noreferrer noopener" target="_blank" href="https://nextbigideaclub.com/magazine/leaders-keep-falling-merger-acquisition-trap-bookbite/53336/"><span xml:lang="EN-US" data-contrast="none">hovered</span></a><span xml:lang="EN-US" data-contrast="auto">&nbsp;around 70%-75%, meaning around three-quarters of M&amp;A deals&nbsp;failed to&nbsp;deliver the expected financial,&nbsp;operational&nbsp;or strategic value post-integration. One of the key reasons so many deals fall apart, as outlined by finance and accounting researchers Baruch Lev and Feng Gu, is that many&nbsp;</span><span xml:lang="EN-US" data-contrast="none">CEOs are incentivized to focus more on M&amp;A completion than M&amp;A success, causing them to prioritize speed&nbsp;over due&nbsp;diligence during the integration phase.</span><span data-ccp-props="{&quot;201341983&quot;:0,&quot;335559740&quot;:312}">&nbsp;</span></p> <blockquote class="main-article-pullquote"> <div class="main-article-pullquote-inner"> <figure> M&amp;A integration -- and, by extension, the success of the M&amp;A deal -- depends less on deal strategy pre-execution and more on governance discipline during execution. </figure> <i class="icon" data-icon="z"></i> </div> </blockquote> </div> <div> <p paraeid="{29035921-10c4-461c-a7eb-d583e3d07ce5}{116}" paraid="1453365582"><span xml:lang="EN-US" data-contrast="auto">M&amp;A integration -- and, by extension, the success of the M&amp;A deal -- depends less on deal strategy pre-execution and more on governance discipline during execution. Therefore, leaders hoping to maximize the potential of any merger or acquisition must prioritize governance maturity. A well-planned, resilient governance structure with clear, well-defined decision rights, system ownership, data&nbsp;management&nbsp;and accountability structures provides visibility&nbsp;into&nbsp;and control&nbsp;over&nbsp;how technology is implemented,&nbsp;managed&nbsp;and evolved in each organization.&nbsp;</span><span data-ccp-props="{&quot;201341983&quot;:0,&quot;335559740&quot;:312}">&nbsp;</span></p> </div> <div> <p paraeid="{29035921-10c4-461c-a7eb-d583e3d07ce5}{130}" paraid="1780881058"><span xml:lang="EN-US" data-contrast="auto">Mature governance frameworks enable leaders to&nbsp;determine&nbsp;optimal&nbsp;ways to align systems,&nbsp;data&nbsp;and operational processes across the two firms. In doing so, they can effectively&nbsp;optimize&nbsp;the merged firm's technology portfolio and realize expected deal value and powerful synergies -- without appreciably increasing disruptions or risk.</span><span data-ccp-props="{&quot;201341983&quot;:0,&quot;335559740&quot;:312}">&nbsp;</span></p> <p paraeid="{29035921-10c4-461c-a7eb-d583e3d07ce5}{130}" paraid="1780881058"><em><span xml:lang="EN-US" data-contrast="none">Rahul&nbsp;Awati&nbsp;is a PMP-certified project manager with IT infrastructure experience spanning storage,&nbsp;compute&nbsp;and enterprise networking.</span>&nbsp; </em></p> </div> </div> M&As are often based on valuation and strategic fit, but post-deal integration -- where governance maturity becomes critical -- determines whether they succeed or fail. https://cdn.ttgtmedia.com/rms/onlineimages/check_g1205300933.jpg https://www.techtarget.com/searcherp/feature/How-governance-maturity-affects-MA-integration-outcomes Wed, 08 Apr 2026 13:47:00 GMT <p>Like it or not, most enterprises are heterogeneous. That is what makes the current vendor agentic AI push so notable. Even in messy, mixed software environments, companies are starting to act as if AI agents can become a normal part of the suite.</p> <p>Salesforce, Oracle, Workday and Zoom all suggest that agentic AI is moving out of the concept stage and into enterprise software itself. The important point is not just that vendors are talking about agents; it is that they increasingly seem to believe agents are ready to become a standard capability that organizations should expect from enterprise software.</p> <p>That is easier said than done.</p> <p>Trust, integration, security and orchestration are still very much in play. But the product direction is becoming harder to miss. Vendors are starting to act as if agentic AI belongs inside the software layer -- not off to the side as some future experiment.</p> <section class="section main-article-chapter" data-menu-title="Salesforce makes the practical case first"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Salesforce makes the practical case first</h2> <p>Salesforce is taking the most practical route of the group. Rather than treating agentic AI as a product within itself, it is integrating Agentforce into its SMB suites as a value add. By <a target="_new" href="https://www.techtarget.com/searchcustomerexperience/news/366640488/Salesforce-adds-Agentforce-agentic-AI-to-SMB-packages">putting prebuilt agents into standard subscription tiers</a>, Salesforce seems to be trying to take some of the mystery out of agentic AI and turn it into another commonplace tool users should increasingly expect from its products.</p> <p>That matters because Salesforce is aiming at everyday busywork -- work that is less strategic and less likely to cause catastrophe if something goes wrong. In that sense, Salesforce makes the first believable phase of agentic AI look less like autonomous decision-making and more like the addition of an assistant to each employee to make work more manageable and streamlined.</p> <p>Salesforce is also starting to give that approach a more explicit operating logic, emphasizing context, control, observability and orchestration as the elements that make agentic deployments work in practice.</p> <div class="extra-info"> <div class="extra-info-inner"> <p></p> <h3 class="splash-heading">4 different routes into suite-based agentic AI</h3> <p>One useful way to read the current wave of announcements is that the vendors are not really making the same pitch.</p> <ul class="default-list"> <li><b>Salesforce</b> is trying to normalize agents by embedding them into familiar product tiers and everyday tasks.</li> <li><b>Oracle</b> is making the broadest claim, tying agents to business objectives and a staged path toward autonomy.</li> <li><b>Workday</b> is grounding its case in trusted HR and finance data, permissions and process logic.</li> <li><b>Zoom</b> is extending the argument into the workflow layer, where conversations and meetings become inputs to finished work.</li> </ul> <p>Seen that way, the story is not simply that AI agents are arriving; it is that vendors are trying to define what kind of suite functionality agents should become first: packaged and practical, broad and strategic, data-grounded or workflow-bridging.</p> </div> </div> </section> <section class="section main-article-chapter" data-menu-title="Oracle goes bigger on ambition"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Oracle goes bigger on ambition</h2> <p>Oracle appears to be diverging from Salesforce's approach in a few important ways. It is introducing <a target="_new" href="https://www.techtarget.com/searcherp/news/366640636/Oracle-calls-Fusion-Agentic-Applications-next-level-AI-for-ERP">22 new agentic AI applications tied to business objectives</a>, whereas Salesforce is integrating Agentforce into existing suites. Oracle also keeps using the language of business objectives, which goes beyond what Salesforce is promising.</p> <p>It is going big rather than narrow.</p> <p>That bigger language matters. Oracle is framing agentic AI not as a helpful add-on, but as a way to move enterprise applications beyond their traditional role as systems of record and toward coordinated action. You do have to wonder, though, whether Oracle is also telling customers something else: Don't worry so much about orchestration, because we will deliver the agents you need inside our own environment.</p> <p>That is where the questions start.</p> <p>Even if those agents come from the same company, how well do they actually work together in parallel without friction? And how far does that confidence travel once those agents have to operate in the more heterogeneous software environments most enterprises actually run?</p> <h3>Trust still has to be earned</h3> <p>Oracle's human-in-the-loop to human-in-the-lead autonomy model also matters. It is a step ladder to agentic AI independence, and it makes adoption feel more manageable by not forcing autonomy from the start. That is logical. Trust has to be earned before agents are granted more independence.</p> <blockquote class="main-article-pullquote"> <div class="main-article-pullquote-inner"> <figure> Trust has to be earned before agents are granted more independence. </figure> <i class="icon" data-icon="z"></i> </div> </blockquote> <p>At the same time, that ladder points to one of the real limits of agentic AI right now. If oversight is required to build trust, then human review can become a resource problem of its own. Vendors know enterprises are not ready to jump straight from AI assistance to full autonomy. Oracle is simply the clearest here about trying to walk customers toward that outcome in stages.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/enterprise_ai_governance_framework-f.png "> <img data-src="https://www.techtarget.com/rms/onlineimages/enterprise_ai_governance_framework-f_mobile.png " class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/enterprise_ai_governance_framework-f_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/enterprise_ai_governance_framework-f.png 1280w" alt="Diagram of an AI governance framework, which depends on controls around data, permissions, oversight and execution across software environments." height="359" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>An enterprise AI governance framework helps explain what vendors still have to solve as they push agents into software suites: data access, permissions, oversight and reliable execution. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> </section> <section class="section main-article-chapter" data-menu-title="Workday grounds the case in data and process"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Workday grounds the case in data and process</h2> <p>Workday is making a different case.</p> <p>To Workday, agentic AI matters less as a flashy interface with specially designed prompts and more as a gateway to maximizing what is achievable from <a target="_new" href="https://www.techtarget.com/searchhrsoftware/news/366640361/Workdays-new-old-CEO-reveals-Sana-agentic-AI-updates">trusted HR and finance data inside a system of record</a>. Its argument is that enterprise AI gets stronger when it sits inside an existing software environment with a trusted data foundation.</p> <p>That is what the system of record means here. The AI is not just generating answers; it is operating in a system that already contains the permissions, workflows, compliance rules and business logic needed to guide usage.</p> <p>Salesforce makes agents feel packaged. Oracle makes them feel expansive. Workday makes them feel integrated, grounded, and, in some ways, less likely to unintentionally wreak havoc.</p> <p>Still, Workday raises its own version of the same larger question. It talks about openness through connectors, but the real value of its AI offering clearly lies in the tight integration of AI within its own environment, guided by trusted HR and finance data.</p> <p>That makes sense. But it also underlines a broader truth: Vendors might talk about openness and interoperability, yet the real competitive fight still seems to rest in how well agents work inside each vendor's own products.</p> </section> <section class="section main-article-chapter" data-menu-title="Zoom pushes agents into the workflow layer"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Zoom pushes agents into the workflow layer</h2> <p>Zoom extends the story beyond classic business apps.</p> <p>What Zoom adds is the idea that agentic AI is not staying inside core enterprise applications. Instead, it is moving into the wider workflow, where work is discussed and then completed.</p> <p>So, this is not just a collaboration and communication software play. It is a play to turn collaboration and communication software into a more integral part of completing tasks and achieving business objectives. Its clearest phrase is the promise to <a target="_new" href="https://www.techtarget.com/searchunifiedcommunications/news/366640476/Zoom-integrates-agentic-AI-across-platform-portfolio">turn conversations and meetings into finished work</a>.</p> <p>That line matters because it suggests that agentic AI has a role to play in collating, summarizing and surfacing insights in ways that otherwise would not be achievable with this kind of automation and smarts. Zoom is trying to bridge the gap between daily communication and collaboration and the wider enterprise application layer.</p> <p>What feels credible there is how AI can achieve specific tasks such as note-taking, summarization and follow-up. What still feels less clear is how all of that ultimately integrates with the broader software environment to contribute to finished work in a reliable way.</p> <p>Even so, Zoom pushes the story beyond the single application. It makes the broader enterprise-software story feel less like a story about single applications and more like a story about bridging the gap between enterprise software platforms to achieve business goals.</p> <div class="youtube-iframe-container"> <iframe id="ytplayer-0" src="https://www.youtube.com/embed/5eQwl9yaEjE?autoplay=0&amp;modestbranding=1&amp;rel=0&amp;widget_referrer=null&amp;enablejsapi=1&amp;origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0"></iframe> </div> </section> <section class="section main-article-chapter" data-menu-title="Different routes, similar destination"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Different routes, similar destination</h2> <p>Taken together, these moves suggest that vendors are trying to reach a similar destination in different ways.</p> <p>Salesforce is trying to make agentic AI a daily fact of life sooner by embedding it into familiar suites and narrower use cases. Oracle is trying to lead customers toward a broader, more autonomous model tied to business objectives. Workday is making the case that agents become more credible when they are grounded in trusted enterprise data and governed by the logic of the application they sit within. Zoom is trying to connect the place where work gets discussed with the place where work gets done.</p> <p>The common thread is not that one vendor has solved agentic AI; it is that vendors increasingly believe agents belong inside the software layer. The harder questions now follow: What kinds of agents are arriving first, where they can be trusted and how far they can move beyond the applications that created them?</p> <p><i>James Alan Miller is a veteran technology editor and writer who leads Informa TechTarget's Enterprise Software group. He oversees coverage of ERP &amp; Supply Chain, HR Software, Customer Experience, Communications &amp; Collaboration and End-User Computing topics.</i></p> </section> Salesforce, Oracle, Workday and Zoom are pushing AI agents into suites and workflows, but each is taking a different path toward practical enterprise adoption. https://cdn.ttgtmedia.com/rms/onlineimages/chatbot_g1199436523.jpg https://www.techtarget.com/searcherp/feature/Inside-the-push-to-turn-AI-agents-into-suite-functionality Wed, 08 Apr 2026 12:58:00 GMT <p>An accounting system controls what's arguably the most critical aspect of any company: money. If this system is threatened, everything else is affected, so CFOs must work with chief information security officers (CISOs) to ensure their company's accounting department is guarding against cybersecurity threats.</p> <p>Common accounting cybersecurity problems include <a href="https://www.techtarget.com/searchsecurity/definition/ransomware">ransomware</a> and <i>privilege creep</i>, in which users who are no longer with the organization can still access systems. When a security event occurs, investigators will examine a company's governance, including frequency of system testing and documented processes, and a company could face negative consequences if its employees have not been following the proper procedures. CFOs must take action before issues arise.</p> <p>Here are five of the most common accounting cybersecurity threats, along with advice on how to mitigate them.</p> <section class="section main-article-chapter" data-menu-title="1. AI-powered email threats"> <h2 class="section-title"><i class="icon" data-icon="1"></i>1.&nbsp;&nbsp;&nbsp;&nbsp; AI-powered email threats</h2> <p><a href="https://www.techtarget.com/searchsecurity/feature/How-to-avoid-phishing-hooks-A-checklist-for-your-end-users">Attempted email hacking</a> has matured. AI tools now enable attackers to study earnings calls, imitate leaders' communication styles and send requests during a company's quarter-end close, when employees are busy and approval pressure is high.</p> <p>It might appear that most CISOs have deployed technical controls to prevent these threats, <a href="https://www.techtarget.com/searchsecurity/tip/Multifactor-authentication-Examples-and-strategic-use-cases">such as multifactor authentication</a> (MFA), access control policies, domain monitoring and email authentication. However, CFOs must also enforce process discipline, including dual authorization on payment changes, mandatory verbal confirmation for new or modified vendor banking details, and system enforcement of separation of duties.</p> </section> <section class="section main-article-chapter" data-menu-title="2. Ransomware"> <h2 class="section-title"><i class="icon" data-icon="1"></i>2.&nbsp;&nbsp;&nbsp;&nbsp; Ransomware</h2> <p>A ransomware group encrypting critical accounting systems stops payroll, stalls reporting and creates regulatory deadline pressure. One compromised endpoint can become a full ERP outage, especially for internally hosted ERP systems. Backups often exist, but they might not have been tested recently, if at all.</p> <p>CISOs and CFOs must work together to <a href="https://www.techtarget.com/searchsecurity/tip/How-to-prevent-and-protect-against-ransomware">prepare for ransomware attacks</a> on accounting systems. They should ensure their company is segmenting finance systems from the rest of the network, maintaining offline or permanent backups, and testing recovery realistically in real-world scenarios.</p> <p>CFOs should ask how long it would take to restore full accounting operations after a complete outage, and if the answer is vague, ensure that those issues are resolved before a ransomware event occurs.</p> </section> <section class="section main-article-chapter" data-menu-title="3. ERP and application vulnerabilities"> <h2 class="section-title"><i class="icon" data-icon="1"></i>3.&nbsp;&nbsp;&nbsp;&nbsp; ERP and application vulnerabilities</h2> <p>Most accounting platforms sit inside larger ERP ecosystems with web interfaces, <a href="https://www.techtarget.com/searchapparchitecture/definition/application-program-interface-API">APIs</a> and third-party integrations. Remote access that requires MFA and specifically defined access controls might be layered in. These technical controls are necessary but can lead to security challenges.</p> <p>Common issues in these environments include missing patches, excessive privileges, weak session controls, integrations that have not been tested since deployment and accounting systems that are no longer supported by the vendor. These vulnerabilities can lead to cybersecurity problems. &nbsp;</p> <p><a href="https://www.techtarget.com/searchcio/tip/Prep-a-compliance-audit-checklist-that-auditors-want-to-see">Compliance audits</a> can create a false sense of security around ERP systems. Annual access reviews and documentation of controls do not go far enough; companies must also conduct meaningful vulnerability and penetration testing against finance systems and simulate how the ERP behaves under actual attack conditions. If leaders don't want to invest in it, or if organizations assume that the vendor or hosting provider is taking care of these issues, they might skip these crucial steps.</p> <p>Every company must have a <a href="https://www.techtarget.com/searchsecurity/tip/Best-practices-for-board-level-cybersecurity-oversight">security committee</a> that sets measurable goals, ensures that independent testing is carried out and holds employees accountable when necessary, and the CFO must have a seat at that table as a decision-maker.</p> </section> <section class="section main-article-chapter" data-menu-title="4. Insider risk and privilege creep"> <h2 class="section-title"><i class="icon" data-icon="1"></i>4.&nbsp;&nbsp;&nbsp;&nbsp; Insider risk and privilege creep</h2> <p>Accounting teams often require higher-level software access, since they add vendors, modify payment details, export reports and adjust journal entries. Accounting employees are also under significant pressure, and risk can arise from fatigue. Other risk factors include poorly designed processes, lack of training and general ignorance involving computer usage.</p> <p>Another major risk factor is privilege creep if &nbsp;employees who have left the company never had their system access revoked. CFOs need to be involved with periodic access reviews, and role-based access policies need to be enforced. Logging should be tied to specific high-risk financial actions and users, and human oversight must be involved.</p> </section> <section class="section main-article-chapter" data-menu-title="5. Cloud accounting software"> <h2 class="section-title"><i class="icon" data-icon="1"></i>5.&nbsp;&nbsp;&nbsp;&nbsp; Cloud accounting software</h2> <p>Many accounting environments now run as cloud-based services, and CFOs and CISOs might assume that the vendor handles security. That assumption is usually incorrect and can lead to problems such as disabled MFA and overly permissive or exposed API tokens.</p> <p>Unless a cloud provider has specifically outlined in a contract that it will take care of security and that security oversight is paid for through specific services, the customer is responsible for it. Company leaders might believe that their job is done because they received a System and Organization Controls report that examines data center controls for third parties. However, it does not present a full picture of security vulnerabilities.</p> <p>If a vendor, such as an identity provider or ERP integration partner, experiences a breach, its security problem will become its clients' security problem. CFOs and CISOs must follow the <a href="https://forensicsinstitute.org/trust-but-verify-your-best-defence-against-fraud/">old security adage:</a> "Trust but verify." Contracts and questionnaires provide a starting point, but what will matter most is whether a vendor's client has built enough resilience to absorb the impact when a third-party failure affects their accounting environment.</p> <p>CISOs and CFOs need to evaluate third-party accounting vendors the way they would evaluate any critical business risk. They should ask to see recent vulnerability and penetration testing results, verify MFA enforcement, review access controls, and understand exactly what the "shared responsibility" cloud model means for their company's specific configuration.</p> <p><i>Kevin Beaver is an independent information security consultant, writer and professional speaker with Atlanta-based Principle Logic, LLC. With more than 30 years of experience in the industry, Beaver specializes in performing vulnerability and penetration tests as well as virtual CISO consulting work.</i></p> </section> AI-powered email threats and ransomware are two of the most common accounting cybersecurity threats, and CFOs must take action to reduce the likelihood of a breach. Learn more. https://cdn.ttgtmedia.com/rms/onlineimages/money_g1255091249.jpg https://www.techtarget.com/searcherp/tip/5-of-the-most-common-accounting-cybersecurity-threats Wed, 01 Apr 2026 10:40:00 GMT <p>Manufacturers were slower than some industries to adopt digital technologies, a gap that became more visible during the COVID-19 pandemic as companies faced supply chain disruptions and shifting operational demands.</p> <p>The pandemic "really exposed the lack of [digital] investments they've made over time," said Sachin Lulla, consulting industrial products sector leader at EY Americas. Companies grew through acquisitions, piling up legacy debt applications that were never integrated -- "and they obviously paid the price for it,'' he said.</p> <p>Now, Lulla said EY is seeing "a massive shift" in how manufacturing companies are thinking about digital and, more importantly, how they are thinking about having a digital and <a href="https://www.techtarget.com/searchenterpriseai/tip/How-to-formulate-a-winning-AI-strategy">AI strategy</a> that has "a clear ROI/business case."</p> <section class="section main-article-chapter" data-menu-title="AI becomes a board issue"> <h2 class="section-title"><i class="icon" data-icon="1"></i>AI becomes a board issue</h2> <p>With the blockbuster debut of <a href="https://www.techtarget.com/whatis/definition/ChatGPT">ChatGPT</a>, AI has become a board-level priority for manufacturers -- a trend reflected in the growing frequency with which manufacturing clients are contacting EY for guidance on AI, Lulla noted.</p> <blockquote class="main-article-pullquote"> <div class="main-article-pullquote-inner"> <figure> Every board is now asking CEOs, 'Do we need a strategy that leverages AI?' Our advice is ... an AI strategy should be linked to overall business outcomes, and every use case must have a clear business case before you pursue it. </figure> <figcaption> <strong>Sachin Lulla</strong>Consulting industrial products sector leader, EY Americas </figcaption> <i class="icon" data-icon="z"></i> </div> </blockquote> <p>"Every board is now asking CEOs, 'Do we need a strategy that leverages AI?'" Lulla said. "Our advice is: They don't need an AI strategy -- they need a digital and AI strategy that are in agreement. An AI strategy should be linked to overall business outcomes for the company, and every use case must have a clear business case before you pursue it."</p> <div class="imagecaption alignRight"> <img src="https://cdn.ttgtmedia.com/rms/onlineimages/lulla_sachin.jpg" alt="Sachin Lulla">Sachin Lulla </div> </section> <section class="section main-article-chapter" data-menu-title="Transformative power of generative AI in manufacturing"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Transformative power of generative AI in manufacturing</h2> <p>Manufacturers are paying attention to AI, particularly to the potentially transformative power of generative AI (<a href="https://www.techtarget.com/searchenterpriseai/definition/generative-AI">GenAI</a>), the technology underlying ChatGPT and other AI-powered assistants.</p> <p><a href="https://www.abiresearch.com/press/strategic-deployment-of-generative-ai-in-manufacturing-will-unlock-us105-billion-added-revenue-by-2033/" target="_blank" rel="noopener">According to ABI Research</a>, the manufacturing industry's investment in GenAI will generate "additional revenues with a significant spike of $4.4 billion from 2026 to 2029. By 2033, revenue added from the use of GenAI in manufacturing will reach $10.5 billion," the firm said.</p> <p>The top reason cited by global manufacturers to use GenAI, according to a <a href="https://go.abiresearch.com/lp-the-state-of-technology-in-the-manufacturing-industry" target="_blank" rel="noopener">2024 survey by ABI</a>, is to identify the root cause of production issues faster than currently possible, followed by the "faster creation of work instructions" and "improved workforce coding skill."</p> <p>AI and digital technologies -- combined with higher employee skill levels -- are already giving the sector a jolt, according to <a href="https://www.mckinsey.com/capabilities/operations/our-insights/adopting-ai-at-speed-and-scale-the-4ir-push-to-stay-competitive?cid=omcknsl-eml-nsl--mck-ext-----&amp;hlkid=1675660fe04a43e9bd30c1a6c03e88d3&amp;hctky=9142176&amp;hdpid=edf49aac-38fe-4a9a-bee4-2e6ee5142b43" target="_blank" rel="noopener">McKinsey</a>. The firm said growth in the U.S. manufacturing sector was stuck at 1.4% over the past two decades: "More recently, AI, digital technologies, sustainable features and higher skills have reinvigorated the market: Over the past five years, U.S. industrials companies have generated total shareholder returns about 400 basis points higher than in the previous 15 years."</p> <p>McKinsey also <a href="https://www.mckinsey.com/capabilities/operations/our-insights/operations-blog/harnessing-generative-ai-in-manufacturing-and-supply-chains" target="_blank" rel="noopener">predicted</a> that generative AI has the potential to make a big difference in several areas of manufacturing, including planning, productivity by using root cause analysis to predict failures and reduce defects, and delivery by helping to get products to customers on time and communicating with them via AI chatbots. "Paired with digital twins, GenAI can create warehouse designs and production scenarios faster,'' the consulting firm said.</p> <div class="imagecaption alignRight"> <img src="https://cdn.ttgtmedia.com/rms/onlineimages/hayden_reese.jpg" alt="Reece Hayden">Reece Hayden </div> <p>Still, it's important to note that manufacturing remains in a relatively early <a href="https://www.techtarget.com/searchenterpriseai/Ultimate-guide-to-artificial-intelligence-in-the-enterprise">AI deployment</a> stage, stressed Reece Hayden, principal analyst at ABI Research, including in the area of generative AI, where, at present, "the only realistic applications for GenAI are currently in the back office with human oversight," he said.</p> <p>However, traditional machine learning (ML) models, such as <a href="https://www.techtarget.com/searchenterpriseai/definition/machine-vision-computer-vision">machine vision</a> and graph-based <a href="https://www.techtarget.com/searchenterpriseai/definition/natural-language-processing-NLP">natural language processing</a>, are beginning to scale, he said.</p> <p>"As the ROI [from AI tools] becomes clearer, the technology matures and manufacturers accelerate digital transformation strategies, these models are increasingly being deployed to support a variety of back-office and even operational use cases," he said.</p> </section> <section class="section main-article-chapter" data-menu-title="AI use cases in manufacturing"> <h2 class="section-title"><i class="icon" data-icon="1"></i>AI use cases in manufacturing</h2> <p><a href="https://www.techtarget.com/searchenterpriseai/feature/GenAI-in-product-manufacturing-cuts-costs-but-adds-risks">Manufacturers are applying AI</a> across both operational and back-office workflows, with the strongest early use cases often focused on productivity, quality, documentation and forecasting.</p> <p>Specific use cases of AI in manufacturing include the following.</p> <h3>1. Cobots and autonomous mobile robots</h3> <p>Collaborative robots (<a href="https://www.techtarget.com/whatis/definition/collaborative-robot-cobot">cobots</a>) and autonomous mobile robots, or AMRs, have already been adopted by manufacturers to enhance and complement the workforce, while reducing errors, increasing speed to value and improving quality, according to Rockwell Automation's "9^th Annual State of Smart Manufacturing" <a href="https://www.rockwellautomation.com/en-us/capabilities/digital-transformation/state-of-smart-manufacturing.html" target="_blank" rel="noopener">report</a>. Some 85% of respondents have already invested or plan to invest in AI/ML in these areas this year.</p> <p>Amazon has deployed hundreds of thousands of robots working in tandem with employees, including a robotic system called Sequoia. Amazon says Sequoia can identify and store inventory at fulfillment centers up to 75% faster and reduce order processing time through a fulfillment center by up to 25%, improving shipping predictability and increasing the number of products available for same-day or next-day shipping.</p> <p>Drones are also gaining traction in the manufacturing sector, according to ABI Research.</p> <div class="imagecaption alignRight"> <img src="https://cdn.ttgtmedia.com/rms/onlineimages/iversen_james.jpg" alt="James Iversen">James Iversen </div> <h3>2. GenAI in PLC coding</h3> <p>Manufacturers that are "extremely digitally mature" are adopting GenAI for programmable logic controller (PLC) coding, said James Iversen, industry analyst in industrial and manufacturing at ABI Research.</p> <p>"With any use case, a company must have correct data inputs and employees who understand the risks of using GenAI," he explained. Not many smaller manufacturers have the right apps, data streams and outputs, he added.</p> <p>Even at sophisticated companies, GenAI must be scrutinized, Iversen warned. "When GenAI writes code for PLCs, it has to be double-checked and triple-checked by coders to make sure there are no hallucinations and it is not adding lines of code that are completely irrelevant."<br><br>Siemens and motion tech company Schaeffler have collaborated on Industrial Copilot to help Schaeffler's automation engineers generate code faster for PLCs and reduce time, effort and the probability of errors. The PLC code is generated through natural language inputs.</p> <p>ABI Research's aforementioned "The State of Technology in the Manufacturing Industry" survey found that 52% of U.S.-based manufacturers believe GenAI can help them fix bugged software code more quickly than currently possible.</p> <h3>3. GenAI in managing inventory levels and purchasing cycles</h3> <p><a href="https://www.techtarget.com/searcherp/tip/Benefits-and-use-cases-for-AI-in-inventory-management">Checking inventory levels</a> of raw materials components in warehouses is another big GenAI use case. "Manufacturers can look at the historical data of how much raw materials cost in the past and can suggest best period times for purchasing,'' Iversen said.</p> <p>AI can also be used to streamline warehouse operations, ensuring the right levels of inventory and that duplicate components are not being purchased, he said.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/8_ai_use_cases_in_manufacturing-f.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/8_ai_use_cases_in_manufacturing-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/8_ai_use_cases_in_manufacturing-f_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/8_ai_use_cases_in_manufacturing-f.png 1280w" alt="AI manufacturing use cases" height="255" width="560"> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <h3>4. Autonomous vehicles</h3> <p>The deployment of autonomous vehicles (AVs) is at varying stages. Automaker Rivian has integrated <a href="https://www.emergingtechbrew.com/stories/2024/06/06/rivian-ai-next-gen-vehicles-wassym-bensaid?mbcid=35630512.182543&amp;mblid=ab14e67d094b&amp;mid=0ee7b8bf9bc73b17e8ebf5a7f0dfe825&amp;utm_campaign=etb&amp;utm_medium=newsletter&amp;utm_source=morning_brew" target="_blank" rel="noopener">AI prediction technology</a> into its R1T pickup truck and R1S SUV and has initiatives underway to integrate traditional AI and GenAI inside its vehicles.</p> <p>And, earlier this year, Tesla announced plans to install a $500 million Dojo supercomputer at its New York gigafactory, which will be used to train AI systems that support autonomous driving. The millions of terabytes of data the Dojo supercomputer processes from the automaker's electric vehicles will help improve the safety and engineering of Tesla's autonomous driving features, the company said.</p> <p>However, the technology remains nascent for AVs due to AI's inability to make cause-effect challenges, according to <a href="https://www.autonews.com/mobility-report/ai-lacks-causal-inference-needed-av-edge-cases" target="_blank" rel="noopener">Automotive News</a>. General Motors, for example, has halted plans to develop its fully autonomous Cruise Origin, which was being designed without a steering wheel or other human controls.</p> <p>British automaker Bentley is also <a href="https://www.carscoops.com/2024/04/bentley-wont-offer-level-3-autonomous-system-because-they-deem-it-too-dangerous/" target="_blank" rel="noopener">exercising caution on AVs</a>, focusing on plans to implement Level 2 autonomous systems, which take over controls, such as assisting with remote parking, steering and managing speed, but require the driver to stay focused on the road at all times.</p> <div class="extra-info"> <div class="extra-info-inner"> <h3 class="splash-heading">What makes an AI use case practical in manufacturing?</h3> <p>The strongest manufacturing AI projects typically share a few characteristics:</p> <ul class="default-list"> <li>a clear operational or financial outcome</li> <li>high-quality, structured data</li> <li>defined human oversight requirements</li> <li>a realistic deployment path inside existing workflows</li> </ul> </div> </div> <h3>5. Forecasting demand to optimize the supply chain</h3> <p>During the COVID-19 pandemic, a food products distributor reimagined its supply chain by implementing <a href="http://www.accenture.com/content/dam/accenture/final/capabilities/strategy-and-consulting/supply-chain---operations/document/forward-looking-supply-chain-using-demand-forecasting.pdf" target="_blank" rel="noopener">demand forecasting</a> instead of relying on historical data. The company worked with Accenture to develop an AI system that utilizes new data and modeling techniques to improve demand sensing. Using internal data, such as sales and inventory, along with external data, including weather and restaurant reservations, the company gained more visibility and flexibility to anticipate supply chain disruptions. <br><br>The AI system has not only enabled the distributor to manage its supply chain more effectively, but also be better prepared for future disruptions.</p> <h3>6. GenAI for documentation</h3> <p>AI can be used to create frontline worker documentation -- i.e., a consolidated list of all machines and standard operating procedures on how to handle issues, Iversen said. A worker can audibly ask or type into a GenAI tool a question about what to do if a machine isn't operating at the correct output, and the tool gives a reason why, he said.</p> <p>"Let's say a machine is overheating, [the tool] will give you step-by-step instructions on here's what you should do,'' he said. "It's a time-saving mechanism to reduce errors in the manufacturing line as it pertains to machines."</p> <h3>7. GenAI in CAD product design</h3> <p>The first manufacturing use case for GenAI software was in computer-aided design (CAD) software, according to Iversen, and now, 70% of manufacturers are using the technology for discrete processes.</p> <p>Manufacturers are seeing a lot of productivity gains here mainly in time savings. "If I was designing a product and didn't want to start from scratch, I can upload the previous designs I've worked on that are similar and add parameters, such as 'don't exceed this amount of material,' or 'it has to be able to withstand this amount of sheer force and strain,'" he said.</p> <p>In response, the GenAI tool produces between one and 100 design solutions that accurately fit into those parameters.</p> <h3>8. Predictive maintenance</h3> <p>Predictive maintenance "is going to be a huge AI use case," Iversen said, and it's been rolled out by a handful of manufacturers. But it's not a top use case yet, in part because it <a href="https://www.techtarget.com/searchbusinessanalytics/feature/Using-simulation-forecasting-in-business-analytics">does not typically require GenAI.</a> "If you have a robust [manufacturing execution system] or data analytics solution, you can already pretty effectively understand when a machine will have downtime, the root cause for why it's occurring and get some insight into how to fix the problem," he said.</p> </section> <section class="section main-article-chapter" data-menu-title="Challenges of implementing AI in manufacturing"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Challenges of implementing AI in manufacturing</h2> <h3>Data quality</h3> <p>Like in any industry, better data management is needed to fuel AI and empower teams. The Rockwell report found that respondents are "using data to fuel AI/ML and optimize processes. However, those surveyed believe their own organizations use less than half of collected data effectively."</p> <p>"AI needs terabytes of data generated by and collected from a broad range of sources: enterprise systems, machine sensors, connectivity infrastructure and human workers," according to the McKinsey report. Indeed, the most advanced front-runners in AI deployments are ahead because they "had the foresight to make investments and take on risks involved in building the data foundations that are needed to power AI technologies and unlock their potential impact," the report stated.</p> <blockquote class="main-article-pullquote"> <div class="main-article-pullquote-inner"> <figure> Focusing on building high-quality, clean, structured, application-specific data sets will help unlock various AI use cases. </figure> <figcaption> <strong>Reece Hayden</strong>Principal analyst, ABI Research </figcaption> <i class="icon" data-icon="z"></i> </div> </blockquote> <p>EY's Lulla agreed. To truly scale AI, you need accurate, trusted data, he said -- and you need to know which data is needed for the business case at hand. When implementing AI for clients, the first thing EY looks at is the business outcome. "Based on that, we define what data we need to deliver on the AI use case, including historical data and its quality," he said. "Most companies don't have the right data, or it takes a lot of manual effort to put that in place."</p> <p>He cited a company EY worked with that built protective sheets for kitchen countertops and was experiencing massive product recalls. "We needed a lot of different data, for example, conditions or parameters that affect the process," Lulla said, to do the analysis. This included temperature, pressure and speed, as well as configuration settings for the equipment, real-time sensor data, historical time-series data, operator event logs and final inspection results.</p> <p>"What we found was the final inspection was done manually and the quality inspectors did not capture reason codes for failure, such as color or gauge defects, and thus, the AI model could not be trained to predict quality problems accurately until the process was fixed to capture this data,'' Lulla said.</p> <h3>Operational risk</h3> <p>ABI Research's Hayden singled out operational risk as the biggest challenge of AI in manufacturing, especially <a href="https://www.techtarget.com/searcherp/tip/Use-cases-for-generative-AI-in-manufacturing">when generative AI is involved</a>.</p> <p>"Most manufacturing operations are critical, which means accuracy, reliability, security, privacy, availability and latency are all vital,'' he said. "Generative AI models remain immature, highly generalized with limited accuracy, which makes them ineffective for these applications."</p> <p>In addition, given the size and memory burden of generative AI models, it is challenging to deploy them at the edge, where most manufacturing applications are deployed, Hayden said, adding that, eventually, GenAI will scale for edge deployments.</p> </section> <section class="section main-article-chapter" data-menu-title="GenAI: Not there yet"> <h2 class="section-title"><i class="icon" data-icon="1"></i>GenAI: Not there yet</h2> <p>There are a lot of applications for GenAI in the areas of machine vision, industrial IoT and digital twins, but for now, Iversen's interviews with manufacturers indicated they are focused on the most "pragmatic use cases," he said -- projects that yield the fastest and best results. "And, right now, they are what will save employees time."</p> <p>He predicted it will be another six months to a year before companies broaden their use of GenAI.</p> <p>Hayden agreed. There are "very, very limited generative AI deployments outside of back office," he said, explaining that GenAI is "not yet suitable for mission-critical use cases." This is because data sets are not sufficient to train and fine-tune GenAI models. Additionally, GenAI is still reliant on humans, "given the high risk of deployment," Hayden said.</p> <p>Eventually, the data bottleneck will be addressed. In the meantime, he advised companies to get their data in order.</p> <p>"Focusing on building high-quality, clean, structured, application-specific data sets will help unlock various AI use cases," he said.</p> <p>Manufacturers are finding the most value in AI when use cases are tied to clear business outcomes, strong data foundations and realistic deployment plans. While some advanced applications remain early, practical uses in areas such as forecasting, documentation, design and maintenance are already showing where AI can improve manufacturing operations.</p> <p><strong>Editor's note:</strong> <em>This article was lightly updated to reflect current AI use cases, examples and deployment considerations in manufacturing. </em></p> <p><i>Esther Shein is a veteran freelance writer specializing in technology and business. Former senior writer at eWeek, she writes news, features, case studies and custom content.</i></p> </section> Manufacturers are moving from AI experimentation to practical use cases that improve productivity, product quality, maintenance and supply chain decision-making. https://cdn.ttgtmedia.com/rms/onlineimages/iot_g1212287865.jpg https://www.techtarget.com/searcherp/feature/10-AI-use-cases-in-manufacturing Tue, 24 Mar 2026 10:50:00 GMT <p>Oracle announced 22 new agentic AI applications consisting of teams of agents that work together to achieve business objectives rather than being limited to narrow tasks. The applications represent a significant leap forward in <a href="https://www.techtarget.com/searcherp/tip/ERP-trends-that-leaders-should-plan-for-in-2026">how AI is used in ERP</a>, Oracle said.</p> <div class="imagecaption alignLeft"> <img src="https://cdn.ttgtmedia.com/rms/onlineImages/mueller_holger.jpg" alt="Holger Mueller, Vice President and Principal Analyst, Constellation Research">Holger Mueller </div> <p>The vendor's claim found support among industry analysts. Holger Mueller, vice president and principal analyst at Constellation Research, said Oracle has moved ahead of its ERP rivals, including market-share leader SAP. "Now we have to see when people go live and humans are supervising multiple agents," Mueller said. He expects competitors like SAP and Workday to have more spring in their steps as they race to match what Oracle has done.</p> <p>In an interview, Chris Leone, Oracle's executive vice president of applications development, said the applications represent an architectural break from Fusion applications' traditional role as systems of record.</p> <p>"It was always on the human to move work forward. If we had to apply judgment or understand a policy, we did that offline. We came back into the system and updated the system of record," Leone said. In contrast, Agentic Applications "understand" the business context, including policies and histories, and can advance work on their own or recommend actions to the user.</p> <p>Leone likened the process of using the agents to a manager assembling a team of experts to address a problem or objective -- say, reducing supplier expenditures by 20%. "We can start to have these specialized agents understand what the process is, understand context, have all the expertise that they need, and then recommend specific actions you need to take to drive work forward," he said.</p> <p>Agents still handle small tasks, but now they can do more by working together to achieve outcomes that serve larger business goals. "Big outcomes are a collection of smaller outcomes," Leone explained. "To hit an earnings-per-share or gross-margin number, you need to do a bunch of smaller things," such as reducing supplier spend by 10% and lead times by a certain percentage or only working with strategic suppliers to reduce risk.</p> <p>A user can run the agents in human-in-the-loop mode that requires them to approve every action recommended by the AI. Another mode, human in the lead, lets AI agents make some decisions but leaves the more important ones to the human user's judgment. "In the future, as customers feel more confident, they can start to run these agentic applications more autonomously to execute work on behalf of the user," Leone said.</p> <p>The applications are expected to be available by April 2.</p> <section class="section main-article-chapter" data-menu-title="Teams of experts"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Teams of experts</h2> <p>Tagged with the new brand name Fusion Agentic Applications, the 22 applications, or "workspaces," are teams of AI agents "with specific roles, expertise, and decision authority to determine why, when, and how work should happen to achieve a given objective," Oracle said in a press release.</p> <p>They cover four broad business functions that each have a dedicated module in the Fusion ERP suite: HR, supply chain, finance and <a href="https://www.techtarget.com/searchcustomerexperience/definition/customer-experience-CX">customer experience</a>. For example, a workforce operations workspace is designed to make workforce management more proactive and intelligent by reducing manual data gathering, speeding up approval of schedule requests and reducing payroll issues. A design-to-source workspace connects engineering, supplier and sourcing functions for improved decision-making and lower costs.</p> <p>A collections application <a href="https://www.techtarget.com/searchcustomerexperience/tip/How-accounts-receivable-AI-increases-cash-flow-and-efficiency">helps finance teams collect cash more quickly</a>, creating a more intelligent, continuous cash flow to improve working capital, Oracle said. A cross-sell workspace purportedly makes campaigns more proactive and revenue more predictable by helping sales teams identify growth opportunities.</p> <p>Collectively, the applications have capabilities in common that help them reach objectives. They work from a shared, persistent context, which enables them to "remember" the original intent and history of previous decisions and actions, which also means users are less likely to have to reconstruct the context at later steps.</p> <p>The applications are constantly reasoning and evaluating situations so they can adjust their actions toward the objective. Oracle also said it built enterprise-grade <a href="https://www.techtarget.com/searchenterpriseai/definition/AI-governance">governance</a> and auditability into the applications to maintain role-based access and approvals throughout each workflow.</p> <div class="imagecaption alignLeft"> <img src="https://cdn.ttgtmedia.com/rms/onlineimages/sommer_brian.jpg" alt="Brian Sommer, TechVentive Founder and President">Brian Sommer </div> <p>Brian Sommer, president of TechVentive, attributed Oracle's success with agentic AI to its broad, integrated suite of "solid" ERP applications and the methodical way it has built a portfolio of special-purpose agents fine-tuned for working within the suite. "They're still offering virtually all of this stuff as part of a standard subscription price, not as an add-on deal, but they're being smart and efficient about how this agentic AI is being deployed, not just grabbing headlines and costs be damned for the customer."</p> <p>But Sommer cautioned that ERP vendors, including Oracle, have yet to achieve the promise of AI that can be trusted to respond appropriately to market triggers that have an impact across a company, such as a rise in interest rates. The new Agentic Applications move Oracle closer, however. "They've got their hands full with so much to do with the more discrete, short-term things," he said. "But they have an architecture where they can make this go live really quick, and I guarantee you their smartest integrator partners are going to be working on those things."</p> </section> <section class="section main-article-chapter" data-menu-title="New Agent Studio features"> <h2 class="section-title"><i class="icon" data-icon="1"></i>New Agent Studio features&nbsp;</h2> <p>The vendor also announced upgrades to its Oracle AI Agent Studio for Fusion Applications expressly to support developing and deploying the new agentic applications.</p> <p>A new application builder works with agents from Oracle, its partners and other vendors. Users interact with an AI-driven natural-language UI to choose agents, compose workflows and connect enterprise data without having to use traditional development tools, according to Oracle. Other additions support orchestrating enterprise-wide workflows that <a href="https://www.computerweekly.com/news/366621159/Oracle-plants-agentic-AI-flag-in-business-process-automation">cross business processes</a>, blending unstructured content with transactional data, maintaining context awareness and monitoring agent performance.</p> <p>The Agentic Applications and Studio upgrades <a target="_blank" href="https://www.oracle.com/uk/ai-world-tour/" rel="noopener">were unveiled</a> at the Oracle AI World Tour conference in London.</p> <p><em>David Essex is an industry editor who creates in-depth content on enterprise applications, emerging technology and market trends for several Informa TechTarget websites.</em></p> </section> Analysts concur that the 22 new applications represent a significant leap from narrowly focused AI to teams of agents that coordinate tasks to achieve business objectives. https://cdn.ttgtmedia.com/rms/onlineimages/chatbot_g1144033172.jpg https://www.techtarget.com/searcherp/news/366640636/Oracle-calls-Fusion-Agentic-Applications-next-level-AI-for-ERP Tue, 24 Mar 2026 03:01:00 GMT <p><iframe title="Plan a multi-agent orchestration framework for scalable AI" allowtransparency="true" height="150" width="100%" style="border: none; min-width: min(100%, 430px); height: 150px;" scrolling="no" data-name="pb-iframe-player" src="https://www.podbean.com/player-v2/?i=i4gsw-1a79770-pb&amp;from=pb6admin&amp;pbad=0&amp;share=1&amp;download=1&amp;rtl=0&amp;fonts=Arial&amp;skin=1&amp;font-color=auto&amp;logo_link=episode_page&amp;btn-skin=2baf9e" loading="lazy"></iframe></p> <p>Implementing <a href="https://www.techtarget.com/searchenterpriseai/definition/agentic-AI">agentic AI</a> has become a priority for enterprise application vendors and owners, but real-world deployments have been limited in scope. In its November 2025 "State of AI" report, McKinsey found only <a target="_blank" href="https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai" rel="noopener">23% of organizations</a> were scaling agentic AI somewhere in their organizations, most were only doing so in one or two business functions, and 39% were just experimenting.</p> <p>Expanding agentic AI throughout an organization is, in large part, a problem of multi-agent orchestration, where AI agents communicate with each other and coordinate their activities across workflows, applications and even corporate firewalls.</p> <p>Some software developers are recommending the adoption of multi-agent frameworks to manage the problem. Organizations can develop their own frameworks or get them from a variety of commercial and open source developers, including AWS and Microsoft.</p> <p>In this episode of <i>Enterprise Apps Unpacked</i>, Peter Hesse, a partner at 10Pearls, a custom software development and consulting company, lays out the steps for developing a multi-agent orchestration framework. He explains why challenges with security, regulatory compliance and performance multiply when agents are deployed on a large scale.</p> <div class="imagecaption alignRight"> <img src="https://cdn.ttgtmedia.com/rms/onlineimages/hesse_peter.jpg" alt="Peter Hesse, 10Pearls partner">Peter Hesse </div> <section class="section main-article-chapter" data-menu-title="Rules for agents to follow"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Rules for agents to follow</h2> <p>Hesse elaborated on a 10Pearls <a target="_blank" href="https://10pearls.com/blog/building-enterprise-ai-agent-frameworks/" rel="noopener">blog post</a> that details the most common problems in deploying agentic AI at scale and the essential elements of an effective framework.</p> <p>Security is a major concern because agents must talk to each other without compromising security. "Think about all of the things that have to do with security -- the triad of confidentiality, integrity, and availability of information," Hesse said. "You want to make sure your communication mechanisms are hardened for that."</p> <p>He said 10Pearls recommends establishing a policy enforcement layer to ensure that business rules and compliance policies are applied equally across all agents in every workflow. "This saves you from having to write the same code into each agent, but instead you have a singular kind of framework or layer to pass everything through to make sure everything's following the rules."</p> <p>Agentic AI has the potential to change how enterprise applications are developed, according to Hesse.</p> <p>"It's going to become less focused on a screen-by-screen user journey approach and more around the creation of services and APIs that are meant to be called by agents, not by people," he said. "It means we have to change the way we think about doing these things and build things more modularly and that are driven more by events rather than mouse clicks and key entries."</p> <p>It also means exposing data and workflows that were never intended to be exposed in the old style of developing applications.</p> <p>Other topics discussed in the podcast include the following:</p> <ul class="default-list"> <li>How a framework can support observability and traceability of agents.</li> <li>Why agents' tendency to work in harmony with each other can make them less resilient in new, large-scale scenarios, and ways to counteract that.</li> <li>Who should be responsible for developing a multi-agent framework.</li> <li>Why being a "double bottom line" company is good for business.</li> </ul> <p><i>David Essex is an industry editor who creates in-depth content on enterprise applications, emerging technology and market trends for several Informa TechTarget websites.</i></p> </section> In this podcast, 10Pearls partner Peter Hesse explains what can go wrong when expanding agentic AI across the enterprise, and why it helps to develop a governance framework. https://cdn.ttgtmedia.com/visuals/digdeeper/4.jpg https://www.techtarget.com/searcherp/podcast/Plan-a-multi-agent-orchestration-framework-for-scalable-AI Mon, 23 Mar 2026 05:00:00 GMT <p>As ERP vendors continue to promote their cloud offerings, COOs and other C-suite leaders who work with ERP software may be considering switching their company’s software to the cloud. Leaders should be aware of the differences between on-premises and cloud software before deciding to move to the cloud.</p> <p>"Vendors are putting their innovation efforts toward their cloud-based solutions rather than on-prem," said Tim Crawford, president of Avoa, an IT consultancy. "Some innovations will be added to the on-prem version, but it's not feasible for things like <a href="https://www.techtarget.com/searchenterpriseai/definition/generative-AI">generative AI</a> to try and add capabilities locally."</p> <p>"There is no doubt that innovation is focused on the cloud across the board, and that customers who are going to be focusing on an on-premises or managed cloud solution long-term will eventually run out of runway in terms of innovation support," said Joshua Greenbaum, principal at Enterprise Applications Consulting.</p> <p>There are compelling reasons companies opt to keep their ERP in-house. The two most obvious are a desire to take full advantage of the sizable investment they've already made and a reluctance to cause stress to employees who are resistant to change.</p> <p>Greenbaum said that while the center of gravity has shifted to the cloud, there is no incentive to kill off on-premises software, either. In fact, Greenbaum said, on-premises ERP is stable and costs very little to maintain, but the maintenance contracts are quite lucrative, so there is almost a disincentive on the part of ERP vendors to migrate off it.</p> <p>Eventually, however, every organization will face a decision to replace its ERP system, and each day it becomes more likely that the cloud wins out.</p> <p>To put the on-premises-versus-cloud debate in context, it's important to remember just how much&nbsp;<a href="https://www.techtarget.com/searcherp/feature/10-top-ERP-systems-CIOs-and-business-leaders-should-consider">ERP systems</a>&nbsp;have become the bedrock in companies. Today's ERP systems have become much more than resource planning tools. They are the connective tissue that links pretty much every core business function. The resulting complexity makes it more critical than ever that, when choosing a flavor of ERP system, organizations focus on their particular strategic requirements and resist being swayed by marketing hype.</p> <p>"Every company has different functional needs they need to think about," said Craig Zampa, a partner in the IT advisory practice at accounting firm Plante Moran. "It shouldn't be deployment model first."</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineImages/ERP_deployment.jpg"> <img data-src="https://www.techtarget.com/rms/onlineImages/ERP_deployment_mobile.jpg" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineImages/ERP_deployment_mobile.jpg 960w,https://www.techtarget.com/rms/onlineImages/ERP_deployment.jpg 1280w" alt="Comparison of cloud ERP vs. on-premises ERP deployment models" height="360" width="519"> <figcaption> <i class="icon pictures" data-icon="z"></i>Cloud ERP is quicker and easier to deploy than on-premises ERP but allows less control and customizability. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <section class="section main-article-chapter" data-menu-title="Cloud ERP vs. on-premises ERP"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Cloud ERP vs. on-premises ERP</h2> <p>ERP has three main deployment models: on premises, cloud-based and hybrid, a combination of the two. Hybrid clouds have always been somewhat of a mushy area. For that reason, this article focuses on comparing on-premises systems with one important cloud computing option, SaaS, in which an organization subscribes to a service delivered over the internet.</p> <p>There are two main types of SaaS. In the multi-tenant model, each customer's data is segregated, but the same application, database and underlying infrastructure serve multiple customers. With single-tenant SaaS, each customer gets its own instance of the application and database.</p> <p>While there are many flavors of cloud -- including hosted, public, managed and hybrid -- SaaS is an increasingly popular option to replace on-premises ERP systems. This article mostly compares the multi-tenant style of&nbsp;<a href="https://www.techtarget.com/searcherp/feature/Fueled-by-SaaS-ERP-for-SMBs-soars-into-the-cloud">SaaS ERP</a>&nbsp;with on-premises ERP. While single-tenant SaaS has much of the scalability, convenience and ease of use of all SaaS applications, it usually adds costs and maintenance responsibilities that are mostly absent from multi-tenant SaaS.</p> <p>With that backdrop, what follows are 12 key differences between SaaS and on-premises ERP systems to consider when choosing between the two.</p> <h3>1. Deployment speed</h3> <p>Right out of the gate, SaaS offers a significant advantage: Whereas on-premises ERP systems typically take more than a year to fully deploy and years to get right, SaaS ERP systems are often ready to go live in three to six months. SaaS applications also tend to be easier for employees to learn to use than on-premises applications, easing the change management and adoption process.</p> <h3>2. Adaptability</h3> <p>While on-premises ERP systems are typically more customizable than their SaaS counterparts, the customizations can be complex and expensive and need to be accounted for when making substantive changes to the system. SaaS ERP products tend to be more cookie-cutter, but they are also relatively easy to manipulate and configure. Plus, because of their constant connectivity, SaaS ERP systems update changes everywhere automatically, while on-premises systems are more likely to run into issues with consistency.</p> <h3>3. System and data control</h3> <p>In a SaaS scenario, the ERP vendor or a third-party cloud provider manages the software and data, which reduces a number of costs associated with on-premises systems, most notably the staff required to maintain them. In contrast, the on-premises model offers a higher degree of control over systems and data.</p> <p>Most cloud-based ERP systems allow some degree of personalization, enabling companies to configure the software to their preferred look and feel, but the ability to make consistent use of custom coding is much more limited with multi-tenant SaaS than with on-premises systems or single-tenant SaaS. Being forced to limit customization brings numerous benefits, such as improved agility,&nbsp;<a href="https://www.techtarget.com/searcherp/feature/7-ways-to-ensure-a-successful-cloud-ERP-implementation">reduced ERP expenses and fewer implementation delays</a>, but it can also limit competitive advantage if the ERP can't fully accommodate features that are unique to the business.</p> <h3>4. Integration</h3> <p>Most ERP vendors, both cloud and on-premises, offer tools for programming the integration to enable data transfer between applications. They also have prebuilt integrations with popular applications.</p> <p>Deployment options have expanded in recent years, and ERP vendors have been eager to satisfy the growing demand for <a href="https://www.techtarget.com/searcherp/definition/hybrid-ERP">hybrid cloud and on-premises</a> architectures. The result has been an explosion in cloud-to-cloud and cloud-to-on-premises integration platforms and tools. It's impossible to make a blanket statement comparing the integration strengths and weaknesses of SaaS vs. on-premises ERP. The choice comes down to the capabilities of specific ERP products.</p> <h3>5. Updates</h3> <p>SaaS-based ERP software generally is updated more frequently than on-premises ERP, sometimes even monthly or weekly. This frees companies from having to schedule and manage updates or fret over out-of-date application modules. It also has the added benefit of easing compliance with changing industry and government regulations. However, it's important to note that the multi-tenant SaaS model also allows organizations minimal input into what upgrades they receive and when.</p> <h3>6. Mobile access</h3> <p>Few areas of the ERP deployment conundrum are as clear-cut as this one. While just about every ERP vendor offers some way to provide mobile access for approvals, notifications and visibility into business operations, setting this up on an on-premises system can mean numerous complications, especially if a third-party mobile platform is needed to serve as the link to the ERP system. Conversely, SaaS ERP products largely offer native mobility supported by a standard mobile application.</p> <h3>7. Performance</h3> <p>For the most part, solidly deployed ERP systems perform well whether they are on-premises or SaaS-based, but there are distinctions. For instance, when internet connectivity is an issue, organizations can temporarily lose access to SaaS applications, while that is highly unlikely to occur with an on-premises system. However, when the internet connection is strong,&nbsp;<a href="https://www.techtarget.com/searcherp/feature/The-8-features-all-enterprise-SaaS-applications-must-have">SaaS applications</a>&nbsp;perform admirably and are immune to the performance issues that bottlenecks on corporate networks can create for on-premises ERP systems.</p> <p>There is another aspect of performance to consider. Cloud has the reach to provide services across the globe instead of being limited to the locations served by the organization's data centers. As companies reduce their data center footprint, this problem only grows. In addition, cloud provides computing and storage resources to scale up or down as an application requires. On-premises systems are less flexible, though that is changing as vendors and third-party service providers add hybrid offerings that bring some cloud capabilities to on-premises ERP.</p> <h3>8. Security and reliability</h3> <p>The need to protect critical data, such as financials, employee information, customer account information and trade secrets, means data security remains an essential ERP requirement. And many organizations have cited a perceived lack of security in SaaS to justify choosing an on-premises system.</p> <p>But, on this topic, one thing has become clear: SaaS providers have staffs committed to doing nothing else but protecting their applications, mindful of the compliance needs of hundreds or even thousands of companies.</p> <p>"That requires an adherence to standards that would outweigh what you'd have in your own data center," Zampa said.</p> <p>Another common concern with any ERP system is downtime caused by software, hardware and infrastructure malfunctions. Operational disruption can translate into hefty financial losses, and cloud vendors' reliance on internet access can be of particular concern to businesses with remote locations or in areas with less reliable network connectivity. However, because of their mandate to support many customers, cloud vendors generally have redundancies and disaster recovery protocols in place to protect data and ensure reliability.</p> <p>Zampa sees that as a serious advantage.</p> <p>"If you're a $100 million manufacturer and managing your own ERP environment and you have one server blow, you're down," he said. "That's not the case with a multi-tenant cloud provider."</p> <h3>9. Payment models</h3> <p>On-premises ERP software is usually priced with a one-time, perpetual license fee paid upfront, plus ongoing support fees, some of which may be negotiable. <a href="https://www.techtarget.com/searcherp/feature/Internal-SaaS-ERP-support-vs-outsourcing-How-to-choose">SaaS ERP systems</a> follow a subscription model with fees that are usually payable by the month or year. SaaS vendors can price their cloud applications based on multiple usage factors, such as the number of users, transaction volume or data quantity.</p> <p>In general, on-premises systems have a higher upfront cost, while SaaS ERP is likely to cost more over time.</p> <h3>10. Total cost of ownership</h3> <p>There are major costs associated with any ERP system, whether it's in the cloud or on premises. However, SaaS ERP software has both cost flexibility and&nbsp;<a href="https://www.techtarget.com/searcherp/feature/SaaS-ERP-systems-can-include-hidden-costs">longer-term costs to consider</a>. The differences are important when looking at SaaS versus on-premises ERP. Here are a few areas where understanding the contrasts can be helpful:</p> <ul class="default-list"> <li><strong>Setup.</strong><strong>&nbsp;</strong>Organizations typically don't have to pay for setting up or installing a cloud system, whereas on-premises deployment of ERP software requires a considerable investment of time and money. Throw in the costs related to buying hardware and servers, paying for facilities, and hiring staff to run and maintain the system, and it's clear on-premises ERP can bring hefty upfront costs. Plus, down the line, the organization will have to absorb the costs of updates. In contrast, updates are automatically included with SaaS ERP.</li> <li><strong>Customization.</strong><strong>&nbsp;</strong>On-premises ERP is generally more customizable but requires additional hardware and possible downtime. Although SaaS ERP systems are less expensive and can be configured fairly quickly to achieve limited customization, on-premises ERP systems work best for companies that need extensive or&nbsp;<a target="_blank" href="https://www.panorama-consulting.com/the-case-for-and-against-erp-customization/" rel="noopener">unique customizations</a>.</li> <li><strong>Support.&nbsp;</strong>SaaS ERP support is usually less expensive than on-premises support, with support typically delivered online and included in the subscription price. Additionally, with on-premises software, organizations might have to pay for additional on-site IT to ensure that the software is functioning properly.</li> </ul> <p>Ultimately, choosing an ERP system is a costly decision that will impact a company for years, so no one wants to get it wrong.</p> <p>"The process of selecting an ERP software platform is absolutely critical to the business, and it's usually an investment of close to or more than a million dollars," Zampa said. "No one's got a million dollars to throw away."</p> <h3>11. Advanced features and customization</h3> <p>Almost all of today's innovation in technologies like AI and <a href="https://www.techtarget.com/searchcio/definition/blockchain">blockchain</a> is taking place in the cloud, which means cloud ERP is likely to have features and functions not available in on-premises versions, or that had to be developed in-house and thus maintained, often at great expense.</p> <p>Many organizations have added deep, industry-specific functionality to their on-premises ERP systems over the course of decades. Much of this customization isn't finding its way to the cloud right away. And as noted above, SaaS ERP is not very customizable.</p> <p>All of this means customizations need to be taken into account when an organization is deciding whether to migrate from on premises to the cloud. The customizations might be too important to give up, even if that means foregoing the leading-edge innovations only available in the cloud.</p> <h3>12. Data cleanliness</h3> <p>Before considering a move to the cloud, organizations need to assess the state of their data.</p> <p>Generative AI models are derived from business data, and AI in general is highly susceptible to the garbage in, garbage out problem. That means data must be cleaned up before any AI processing can be done on it.</p> <p>There is also the issue of <a href="https://www.techtarget.com/searchdatamanagement/definition/data-governance">data governance</a>. Government regulations might prohibit some ERP data from being stored in the cloud. If the limited data is considerable or essential to the organization's business, it might not be able to move to cloud ERP at all, making the other difference with on-premises ERP less relevant.</p> </section> <section class="section main-article-chapter" data-menu-title="How to determine which type of ERP is best for your use case"> <h2 class="section-title"><i class="icon" data-icon="1"></i>How to determine which type of ERP is best for your use case</h2> <p>Zampa's advice above bears repeating: Organizations shouldn't buy ERP for the deployment model and instead should focus on their functional needs. That means finding the ERP products with the features and functions that best meet those needs.</p> <p>But as a practical matter, the decision process might point to either cloud or on-premises ERP, since some ERP features do, in fact, depend on the deployment model. Generally, COOs who are concerned about upfront costs and lead time, or need specific, typically cloud-centric technologies like AI should look first at SaaS ERP. In contrast, those that need more control over the location of their ERP, perhaps for security, performance or integration reasons, or have a strong need for customization, should lean toward on-premises ERP.</p> <p>The cloud vs. on-premises ERP choice may soon be made for them, however. Open-ended deployment decisions are mostly the privilege of organizations that are buying their first ERP or perhaps adding systems for new divisions or overseas locations. With more ERP vendors shutting down development of their on-premises ERP and putting all their investments into cloud versions, soon the only people choosing on-premises ERP will be those who already have one, and the real choice will be when, and how much, of their ERP system to move to the cloud.</p> <p><i>Andy Patrizio is a technology journalist with almost 30 years' experience who is currently based in southern California. Tony Kontzer was a California-based freelance journalist who covered technology for more than 20 years.</i><i> </i></p> <p><b>Editor's note: </b><i>This article was expanded, edited and republished to improve the reader experience.</i></p> </section> Understanding the differences between on-premises ERP and cloud ERP, especially multi-tenant SaaS, is critical in buying decisions. Here's how they compare in 12 important areas. https://cdn.ttgtmedia.com/visuals/searchSalesForce/marketing_auto_software/salesforce_article_022.jpg https://www.techtarget.com/searcherp/feature/The-differences-between-on-premises-and-cloud-ERP-software Thu, 19 Mar 2026 13:00:00 GMT <p>Enterprise employees now routinely access corporate systems from devices and applications that operate well outside traditional network boundaries.</p> <p>Employees connect from personal laptops, mobile devices and cloud services that sit beyond the boundaries of the traditional enterprise firewall. In many environments, the infrastructure itself no longer defines the limits of enterprise systems.</p> <p>As a result, governance is shifting toward identity systems and policy frameworks that determine how users, devices and applications interact with enterprise resources. As traditional network boundaries fade, <a href="https://www.techtarget.com/searchsecurity/feature/identity-new-perimeter-enterprise-security">identity is increasingly becoming the new security perimeter</a> for enterprise systems.</p> <section class="section main-article-chapter" data-menu-title="Identity policies increasingly govern application access"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Identity policies increasingly govern application access</h2> <p>Enterprises no longer need complete control over an endpoint to protect sensitive data in BYOD environments. Take <a href="https://www.techtarget.com/searchmobilecomputing/tip/How-to-use-Intune-app-protection-without-MDM-enrollment">Intune mobile application management without enrollment</a>, for example: It enables IT teams to provide access to corporate data, but only within approved applications. This creates a kind of firewall between approved and unapproved apps, allowing users to keep their devices otherwise unmanaged.</p> <p>Enabling corporate and personal environments to coexist on the same device can be a win-win, strengthening governance and data protection while still giving employees the freedom to use their personal devices without intrusive corporate controls.</p> <p>Intune app protection limits access to corporate resources to only those applications permitted by IT policy. It does this by enforcing identity-based controls tied to individual user credentials rather than the device itself.</p> <p>Rather than evaluating device compliance, IT can require that only apps with Intune app protection policies can access corporate resources through Conditional Access. In this model, the device becomes less important than the identity and policies governing how applications access corporate data.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/zero_trust_vs_perimeter_based_security-f.png "> <img data-src="https://www.techtarget.com/rms/onlineimages/zero_trust_vs_perimeter_based_security-f_mobile.png " class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/zero_trust_vs_perimeter_based_security-f_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/zero_trust_vs_perimeter_based_security-f.png 1280w" alt="Diagram comparing infrastructure-based IT control with identity-based policy control" height="324" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>Traditional network perimeters are giving way to identity-based access controls as users, devices and applications operate outside the corporate firewall. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <blockquote class="main-article-pullquote"> <div class="main-article-pullquote-inner"> <figure> Enterprises no longer need complete control over an endpoint to protect sensitive data in BYOD environments. </figure> <i class="icon" data-icon="z"></i> </div> </blockquote> </section> <section class="section main-article-chapter" data-menu-title="Governance extends into collaboration platforms"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Governance extends into collaboration platforms</h2> <p>Collaboration and communications platforms are becoming central hubs for work that goes far beyond chatting, messaging and calling. Increasingly, they are where business processes unfold and where important organizational data flows.</p> <p>That reality means the information moving through these platforms must meet regulatory, legal and security obligations.</p> <p>As a result, monitoring for compliance, security and investigative purposes becomes a necessary component of these tools and the workflows they support. These governance considerations are part of the reality of any core enterprise system -- which collaboration platforms increasingly are.</p> <p>As <a href="https://www.techtarget.com/searchunifiedcommunications/answer/Can-Microsoft-Teams-chat-be-monitored">Teams becomes central to business communications</a>, organizations must balance collaboration with regulatory, legal and security obligations.</p> <p>This oversight can also rely on identity-based policy controls. Identity roles help determine both who can access and participate in communications and who has the authority to monitor activity or enforce compliance policies within the collaboration environment.</p> <div class="extra-info"> <div class="extra-info-inner"> <p></p> <h3 class="splash-heading">Identity is becoming the new security perimeter</h3> <p>Enterprise security strategies historically relied on well-defined network boundaries. Organizations protected internal systems with firewalls and assumed users inside the network could be trusted.</p> <p>That model has largely disappeared.</p> <p>Employees now work from home, on mobile devices and across cloud services outside traditional networks. Identity credentials and authentication systems now determine who can access enterprise resources.</p> <p>Modern security frameworks, such as zero trust, rely on verifying identity and evaluating context for every access request rather than trusting a user's network location.</p> </div> </div> </section> <section class="section main-article-chapter" data-menu-title="Workforce systems help define enterprise identity"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Workforce systems help define enterprise identity</h2> <p>Human resource information systems (HRISes) aren't just repositories for employee records used in onboarding, benefits administration, talent management or offboarding. As the <a href="https://www.techtarget.com/searchhrsoftware/feature/HRIS-vs-HRMS-vs-HCM-Key-differences-and-similarities">system of record for employee data</a>, an HRIS frequently feeds that information into other systems across the organization, including applications used by finance and IT.</p> <p>In that sense, workforce systems don't just track employee information; they help define the identity context in which enterprise access decisions are made. Employee records establish roles, responsibilities and organizational relationships that identity systems can use to determine which systems people can access and which actions they are allowed to perform.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineImages/hrsoftware-core_software.jpg"> <img data-src="https://www.techtarget.com/rms/onlineImages/hrsoftware-core_software_mobile.jpg" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineImages/hrsoftware-core_software_mobile.jpg 960w,https://www.techtarget.com/rms/onlineImages/hrsoftware-core_software.jpg 1280w" alt="Diagram showing core HR software components such as employee records, payroll and job roles" height="408" width="520"> <figcaption> <i class="icon pictures" data-icon="z"></i>HR systems often serve as the system of record for employee identity data that flows into other enterprise systems. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <div class="extra-info"> <div class="extra-info-inner"> <p></p> <h3 class="splash-heading">How HR systems influence enterprise access decisions</h3> <p>In many organizations, HR platforms serve as the authoritative source for workforce identity information. Employee records define attributes such as job title, department and reporting structure. Identity platforms use that information to provision accounts and assign permissions across enterprise systems.</p> <p>When employees change roles or leave the organization, those HR records can trigger automated updates to application access across the enterprise environment. This approach helps organizations maintain consistent governance across cloud platforms, collaboration tools and enterprise applications.</p> </div> </div> </section> <section class="section main-article-chapter" data-menu-title="Identity as the enterprise control layer"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Identity as the enterprise control layer</h2> <p>Taken together, these shifts point to a broader architectural change: Enterprise governance is no longer defined solely by infrastructure boundaries, devices or application deployments. Instead, identity systems increasingly function as the policy layer that connects them.</p> <p>Identity policies help determine which applications users can access, which devices are permitted to connect, how collaboration environments are governed and how access decisions propagate across enterprise systems.</p> <p>As enterprise technology environments continue to expand across cloud services, personal devices and AI-driven tools, identity is quietly emerging as the operational control plane for enterprise IT.</p> <p><i>James Alan Miller is a veteran technology editor and writer who leads Informa TechTarget's Enterprise Software group. He oversees coverage of ERP &amp; Supply Chain, HR Software, Customer Experience, Communications &amp; Collaboration and End-User Computing topics.</i></p> </section> Identity policies increasingly govern how users access enterprise apps, devices and collaboration tools, shifting enterprise control from infrastructure to identity systems. https://cdn.ttgtmedia.com/rms/onlineimages/keys_a404751193.jpg https://www.techtarget.com/searcherp/feature/Identity-is-quietly-becoming-enterprise-ITs-control-plane Tue, 17 Mar 2026 17:26:00 GMT <p>Some procurement tasks, such as analyzing supplier insurance policies and risk assessments, might be a good fit for generative AI (GenAI). Chief procurement officers and any other C-suite members who work on procurement should learn about the specific use cases that GenAI might be a good fit for, as well as the <a href="https://www.techtarget.com/searchenterpriseai/feature/Smarter-robots-Agentic-and-physical-AI-converge-in-business">risks that companies should guard against</a>.</p> <p>Procurement teams spend much of their time working with documents, including requests for proposals (<a href="https://www.techtarget.com/searchitchannel/definition/request-for-proposal">RFPs</a>) and price quotes, along with purchase orders, contracts and service agreements. GenAI can carry out tasks such as creating a first draft of an RFP. Since procurement has long struggled with a lack of resources, generative AI could help procurement teams save time.</p> <p>Below are some use cases--along with the benefits and the risks--of using generative AI in procurement.</p> <section class="section main-article-chapter" data-menu-title="5 use cases for generative AI in procurement"> <h2 class="section-title"><i class="icon" data-icon="1"></i>5 use cases for generative AI in procurement</h2> <p>Five practical applications where <a href="https://www.techtarget.com/searcherp/tip/Benefits-and-use-cases-of-AI-in-procurement">GenAI could be potentially useful</a> to a procurement team include the following.</p> <h3>1.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Supplier messages and RFP development</h3> <p>GenAI can draft text, such as supplier emails, RFPs and agreements, by drawing on information from past documents and organizational templates. The output still needs human review and refinement, but generative AI can provide a human employee with a draft to work from.</p> <h3>2.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Contract review and summarization</h3> <p>Reading, extracting information from and comparing terms between hundreds of supplier agreements takes up a large portion of a procurement manager's day. Generative AI can scan contracts and identify non-standard clauses, flag potential compliance issues and summarize any risks.</p> <p>GenAI often does well at identifying patterns across document sets, such as audit reports or renewal terms, across multiple vendors. The technology can identify whether any reports are concerning or whether agreements lack important text, such as indemnification clauses.</p> <h3>3.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Spend analysis and insights</h3> <p>Conventional spend analytics require line items to be categorized manually and aggregated. Generative AI does not require that degree of organization to analyze spending patterns, identify anomalies and, most usefully, generate natural language explanations of any anomalies.</p> <p>GenAI's capabilities can be particularly useful for <i>tail spend</i>--the small-value purchases that individually don't justify the procurement team's attention but add up to a significant proportion of expenses. For example, generative AI can draft a message to tail spend suppliers.</p> <h3>4.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Supplier risk assessment</h3> <p>A diligent procurement team must <a href="https://www.techtarget.com/searcherp/feature/8-key-supplier-relationship-management-strategies">monitor the financial health of suppliers</a>, along with their operational capacity and their history of regulatory compliance. These processes typically happen only periodically--sometimes just annually--instead of continuously.</p> <p>GenAI can gather and <a href="https://www.techtarget.com/searcherp/tip/4-benefits-of-implementing-automation-in-procurement">synthesize supplier risk data through automated analysis</a>, market intelligence and performance metrics. The technology can process information such as news feeds, financial reports and regulatory filings to assess the stability of suppliers, then recommend action if needed.</p> <p>Generative AI can also monitor mid-tier and smaller suppliers, which normally don't receive dedicated relationship management.</p> <h3>5.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Purchase requisition support</h3> <p>Requisitions that fall outside standard procurement workflows can create bottlenecks and compliance issues. An AI assistant can advise workers with unusual requests about supplier selection and can check that purchases align with existing contracts and policies.</p> <p>GenAI can also send messages to suppliers to confirm specifications, ask for quotes and negotiate basic terms.</p> </section> <section class="section main-article-chapter" data-menu-title="The benefits of using generative AI for procurement"> <h2 class="section-title"><i class="icon" data-icon="1"></i>The benefits of using generative AI for procurement</h2> <p>Generative AI can help procurement teams carry out tasks that they otherwise wouldn't have time to do. For example, it enables procurement workers to analyze and optimize categories that often didn't receive attention because of their modest spend.</p> <p>GenAI can also help procurement employees improve their business decisions. For example, a human employee can prepare for a negotiation by having generative AI tool analyze historical pricing, market data, suppliers' financial information and macroeconomic trends. A human employee would potentially only gather that amount of data for a major contract, but GenAI can synthesize that information prior to all negotiations.</p> </section> <section class="section main-article-chapter" data-menu-title="The risks of using generative AI for procurement"> <h2 class="section-title"><i class="icon" data-icon="1"></i>The risks of using generative AI for procurement</h2> <p>However, chief procurement officers might be, understandably, concerned that <a href="https://www.techtarget.com/searcherp/tip/5-challenges-of-using-AI-in-procurement">AI-generated outputs could contain errors</a> or that the technology could misinterpret business context. AI hallucinations that occur in the preparation of a commercial contract could have serious consequences.</p> <p>Data privacy and intellectual property, such as proprietary supplier information, also require safeguards. Generative AI use in procurement must include the proper access controls and audit trails.</p> <p>Retrieval-augmented generation (<a href="https://www.techtarget.com/searchenterpriseai/definition/retrieval-augmented-generation">RAG</a>) architectures can help address several governance concerns by ensuring that GenAI responses are based on organizational documents instead of relying solely on the training data for a model. For example, if a procurement manager asks about contract terms or supplier analysis, RAG retrieves the information from a secure internal document repository instead of drawing on public training sets.</p> <p>A RAG architecture helps ensure that proprietary information is kept secure and that audit trails are available, as users can trace each recommendation back to specific source documents.</p> <p>RAG doesn't eliminate the need for data quality management or human review. However, it substantially reduces the risks of hallucination and intellectual property leakage.</p> </section> <section class="section main-article-chapter" data-menu-title="How to begin implementing generative AI for procurement"> <h2 class="section-title"><i class="icon" data-icon="1"></i>How to begin implementing generative AI for procurement</h2> <p>Procurement teams should begin using GenAI by launching well-scoped pilots in areas where mistakes will result in limited consequences.</p> <p>Contract summarization and spend analysis are good potential starting points because human employees can easily check the outputs against source documents.</p> <p>The team should <a href="https://www.forbes.com/sites/delltechnologies/2025/04/15/generative-ai-kpi-playbook-measure-what-you-manage/">establish KPIs</a> before implementation and build governance frameworks that define quality and compliance standards before employees start using the technology.</p> <p>Most important is treating early generative AI deployment as a learning exercise. The technology's output will likely improve, but the procurement team must develop the processes and judgment to deploy it effectively. Careful experimentation is a good approach.</p> <p><i>Donald Farmer is a data strategist with 30-plus years of experience, including as a product team leader at Microsoft and Qlik. He advises global clients on data, analytics, AI and innovation strategy, with expertise spanning from tech giants to startups. He lives in an experimental woodland home near Seattle.</i></p> </section> Procurement teams spend much of their time working with documents, and generative AI can carry out tasks such as creating a first draft of an RFP. Learn about use cases and risks. https://cdn.ttgtmedia.com/rms/onlineimages/code_g1287248739.jpg https://www.techtarget.com/searcherp/tip/5-top-generative-AI-use-cases-in-procurement Thu, 12 Mar 2026 15:13:00 GMT <p>Material requirements planning (MRP) is a system for calculating the materials and components needed to manufacture a product. It consists of three primary steps: taking inventory of the materials and components on hand, identifying which additional ones are needed and then scheduling their production or purchase.</p> <p>Chief operating officers (COOs), chief supply chain officers (CSCOs) and any other C-suite members who work on the supply chain must ensure their companies are carrying out MRP in the proper way and should consider whether the technology they are using to carry out MRP is meeting their organization’s needs.</p> <section class="section main-article-chapter" data-menu-title="Why is MRP important?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Why is MRP important?</h2> <p>MRP, which is done primarily <a href="https://www.techtarget.com/searcherp/tip/Top-MRP-software-for-you-to-try">through specialized software</a>, helps ensure that the right inventory is available for the production process exactly when it is needed and at the lowest possible cost. As such, MRP improves the efficiency, flexibility and profitability of manufacturing operations. It can make factory workers more productive, improve product quality and minimize material and labor costs. MRP also helps manufacturers respond more quickly to increased demand for their products and avoid production delays and inventory stockouts that can result in lost customers, which in turn contributes to revenue growth and stability.</p> <p>MRP is widely used by manufacturers and has undeniably been one of the key enablers in the growth and wide availability of affordable consumer goods and, consequently, has raised the standard of living in most countries. Without a way to automate the complex calculations and <a href="https://www.techtarget.com/searchdatamanagement/definition/data-management">data management</a> of MRP processes, it is unlikely that individual manufacturers could have scaled up operations as rapidly as they have in the half century since MRP software arrived.</p> <div class="youtube-iframe-container"> <iframe id="ytplayer-0" src="https://www.youtube.com/embed/Dis3UYcEXVw?autoplay=0&amp;modestbranding=1&amp;rel=0&amp;widget_referrer=null&amp;enablejsapi=1&amp;origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0"></iframe> </div> </section> <section class="section main-article-chapter" data-menu-title="How does MRP work?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>How does MRP work?</h2> <p>MRP uses information from the bill of materials (<a href="https://www.techtarget.com/searcherp/definition/bill-of-materials-BoM">BOM</a>), inventory data and the <a href="https://www.techtarget.com/searcherp/tip/MRP-vs-MPS-What-are-the-differences">master production schedule</a> to calculate the required materials and when they will be needed in the manufacturing process.</p> <p>The BOM is a hierarchical list of all the materials, subassemblies and other components needed to make a product, along with their quantities, each usually shown in a parent-child relationship. The finished good is the parent at the top of the hierarchy.</p> <p>The inventory items in the BOM are classified as either&nbsp;<em>independent demand</em>&nbsp;or&nbsp;<em>dependent demand</em>. An independent demand item is the finished good at the top of the hierarchy.&nbsp;Manufacturers determine its amount by considering confirmed orders and examining market conditions, past sales and other indicators to create a forecast, then decide how many to make to meet the expected demand.</p> <p>Dependent demand items, in contrast, are the raw materials and components needed to make the finished product. For each of these items, demand depends on how many are needed to make the next-highest component in the BOM hierarchy.</p> <p>MRP is the system most companies use to track and manage all of these dependencies and to calculate the number of items needed by the dates specified in the master production schedule. To put it another way, MRP is an inventory management and control system for ordering and tracking the items needed to make a product.</p> <p>Lead time -- the period from when an order is placed and the item delivered -- is another key concept in MRP. There are many types of lead times. Two of the most common are material lead time (the time it takes to order materials and receive them) and factory or production lead time (how long it takes to make and ship the product after all materials are in). Customer lead time denotes the time between the customer order and final delivery. The MRP system calculates many of these lead times, but some are chosen by the operations managers and entered manually.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/erp-bill_of_materials_2.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/erp-bill_of_materials_2_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/erp-bill_of_materials_2_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/erp-bill_of_materials_2.png 1280w" alt="Diagram of a multilevel bill of materials (BOM)" height="465" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>The bill of materials specifies the items needed to make a product and is a key data source in MRP. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> </section> <section class="section main-article-chapter" data-menu-title="MRP in manufacturing"> <h2 class="section-title"><i class="icon" data-icon="1"></i>MRP in manufacturing</h2> <p>MRP is essential to the efficiency, effectiveness and ultimately the profitability of a manufacturing operation. Without the right raw materials and components on hand, manufacturers can't hope to keep up with the demand for products at the optimal cost and quality. They will also be less able to respond to fluctuations in demand by adjusting production.</p> <p>MRP can also make the later stages of production, such as assembly and packaging, proceed more smoothly and predictably by removing most of the uncertainty over inventory and minimizing the time needed to manage it.</p> <p>MRP is useful in both&nbsp;<a href="https://www.techtarget.com/searcherp/definition/discrete-manufacturing">discrete manufacturing</a>, in which the final products are distinct items that can be counted -- such as bolts, subassemblies or automobiles -- and&nbsp;<a href="https://www.techtarget.com/searcherp/definition/process-manufacturing">process manufacturing</a>, which results in bulk products, including chemicals, soft drinks and detergent, that can't be separately counted or easily broken down into their constituent parts.</p> </section> <section class="section main-article-chapter" data-menu-title="Benefits of MRP"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Benefits of MRP</h2> <p>The primary objective of MRP is to make sure that materials and components are available when needed in the production process and that manufacturing takes place on schedule. <a href="https://www.techtarget.com/searcherp/tip/Benefits-of-MRP-software">Additional benefits of MRP</a> are as follows:</p> <ul class="default-list"> <li>Reduced customer lead times to improve customer satisfaction.</li> <li>Reduced inventory costs.</li> <li>Effective <a href="https://www.techtarget.com/searcherp/definition/inventory-management">inventory management</a> and optimization -- by acquiring or manufacturing the optimal amount and type of inventory, companies can minimize the risk of stock-outs, and their negative impact on customer satisfaction, sales and revenue, without spending more than necessary on inventory.</li> <li>Improved manufacturing efficiency by using accurate production planning and scheduling to optimize the use of labor and equipment.</li> <li>Improved labor productivity.</li> <li>More competitive product pricing.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="Disadvantages of MRP"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Disadvantages of MRP</h2> <p>MRP has drawbacks, including the following:</p> <ul class="default-list"> <li>Oversupply of inventory. While MRP is designed to ensure adequate inventory levels at the required times, companies can be tempted to hold more inventory than is necessary, which COOs and CSCOs may find drives up inventory costs. An MRP system anticipates shortages sooner, which can lead to overestimating inventory lot sizes and lead times, especially in the early days of deployment before users gain the experience to know the actual amounts needed.</li> <li>Lack of flexibility. MRP is also somewhat rigid and simplistic in how it accounts for lead times or details that affect the master production schedule, such as the efficiency of factory workers or issues that can delay delivery of materials.</li> <li>Data integrity requirements. MRP is highly dependent on having accurate information about key inputs, especially demand, inventory and production. If one or two inputs are inaccurate, errors can be magnified at later stages. Data integrity and data management are thus essential to effective use of MRP systems.</li> </ul> <p>To address these shortcomings of MRP, many manufacturers use&nbsp;advanced planning and scheduling (APS)&nbsp;software, which uses sophisticated math and logic to provide more accurate and realistic estimates of lead times. Unlike most MRP systems, APS software accounts for production capacity, which can have a significant impact on availability of materials.</p> </section> <section class="section main-article-chapter" data-menu-title="History of MRP"> <h2 class="section-title"><i class="icon" data-icon="1"></i>History of MRP</h2> <p>The seeds of MRP were planted early in the 20th century with the development of new models for optimizing manufacturing. In 1913, American production engineer Ford Whitman Harris developed the calculation known as economic order quantity, the amount that minimizes the cost of ordering and storing a good. Concurrently, the mass-production system invented by Henry Ford showed the value of having strict controls over the flow of materials through an assembly line. Another key driver of industrial efficiency came from the scientific management theories of Frederick Taylor, which included techniques for production planning and control and for improving the efficiency of material handling.</p> <p>With the advent of computers, systems for optimizing the manufacturing process entered a new era. When mainframe computers became commercially available in the 1950s, programmers at manufacturing companies began developing custom software to manage BOMs, inventory, production and scheduling.</p> <p>It wasn't until the 1960s, however, that the field got its modern name. That's when a small group of influential engineers championed an integrated system of computerized planning they dubbed material requirements planning. In 1964, IBM engineer Joseph Orlicky developed and formalized MRP after he studied the Toyota Production System, which was the model for the&nbsp;<a href="https://www.techtarget.com/searcherp/definition/lean-production">lean production</a>&nbsp;methodology. Then, in 1967, Orlicky's IBM colleague, Oliver Wight, co-wrote a book on production and inventory control with George Plossl, a mechanical engineer and management consultant. The three continued to collaborate and today are usually cited as the pioneers of MRP.</p> <p>It's important to note that MRP and lean production are not the same, despite their connection in Orlicky's pioneering work. In fact, they are considered by many practitioners to be antithetical, though some say MRP can help with lean production. MRP is considered a "push" production planning system -- inventory needs are determined in advance, and goods produced to meet the forecasted need -- while lean is a "pull" system in which nothing is made or purchased without evidence of actual -- not forecasted -- demand.</p> <p>Orlicky's ideas spread rapidly throughout the manufacturing sector after the 1975 publication of his book,&nbsp;<em>Material Requirements Planning: The New Way of Life in Production and Inventory Management. </em>By the early 1980s, there were hundreds of commercial and homegrown MRP software programs.</p> <p>MRP also received a major boost in the 1970s from the educational efforts of the American Production and Inventory Control Society (APICS), after Orlicky, Plossl and Wight pushed the association to evangelize for MRP. APICS became the main source of MRP education and certification and continues in that role today, having expanded over the decades into operations management and <a href="https://www.techtarget.com/searcherp/Guide-to-supply-chain-management">supply chain management</a>.</p> <p>Orlicky died in 1986. A second edition of his book, updated by Plossl, was released in 1994. The current version,&nbsp;<em>Orlicky's Material Requirements Planning, Third Edition</em>&nbsp;is a 2011 update by consultants Carol Ptak and Chad Smith. It adds advice on how to use MRP to run a "demand-driven" planning process that uses actual sales orders, rather than the typical MRP method of a sales forecast, to calculate material requirements. Called demand-driven material requirements planning (DDMRP), this newer "pull" approach is controversial and viewed by some as a violation of important principles established by Orlicky.</p> </section> <section class="section main-article-chapter" data-menu-title="MRP vs. ERP"> <h2 class="section-title"><i class="icon" data-icon="1"></i>MRP vs. ERP</h2> <p>An extension of MRP, developed by Wight in 1983 and called manufacturing resource planning (MRP II), broadened the planning process to include other resources in the company, such as financials, and added processes for product design, capacity planning, <a href="https://www.techtarget.com/whatis/definition/cost-management">cost management</a>, shop floor control and&nbsp;<a href="https://www.techtarget.com/searcherp/definition/sales-and-operations-planning-SOP">sales and operations planning</a>, among many others.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineImages/erp-mrp_vs_mrpii_vs_erp-f.png"> <img data-src="https://www.techtarget.com/rms/onlineImages/erp-mrp_vs_mrpii_vs_erp-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineImages/erp-mrp_vs_mrpii_vs_erp-f_mobile.png 960w,https://www.techtarget.com/rms/onlineImages/erp-mrp_vs_mrpii_vs_erp-f.png 1280w" alt="How MRP differs from MRP II and ERP" height="541" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>MRP II expanded MRP to other business functions and was renamed ERP. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <p>In 1990, the analyst firm Gartner coined the term enterprise resource planning (<a href="https://www.techtarget.com/searcherp/definition/ERP-enterprise-resource-planning">ERP</a>) to denote a still more expanded and generalized type of MRP II that took into account other major functions of a business, such as accounting, human resources and&nbsp;<a href="https://www.techtarget.com/searcherp/definition/supply-chain-management-SCM">supply chain management</a>, all of it managed in a centralized database. Both MRP and MRP II are considered direct predecessors of ERP.</p> <p>ERP quickly expanded to other industries, including services, banking and retail, that did not need an MRP component. However, MRP is still an important part of the ERP software used by manufacturers.</p> </section> Material requirements planning (MRP) is a system for calculating the materials and components needed to manufacture a product. https://cdn.ttgtmedia.com/visuals/digdeeper/4.jpg https://www.techtarget.com/searcherp/definition/material-requirements-planning-MRP Tue, 10 Mar 2026 11:00:00 GMT <p><iframe title="Direct materials sourcing technology a hub for manufacturers" allowtransparency="true" height="150" width="100%" style="border: none; min-width: min(100%, 430px); height: 150px;" scrolling="no" data-name="pb-iframe-player" src="https://www.podbean.com/player-v2/?i=3w7rz-1a63b1b-pb&amp;from=pb6admin&amp;pbad=0&amp;share=1&amp;download=1&amp;rtl=0&amp;fonts=Arial&amp;skin=1&amp;font-color=auto&amp;logo_link=episode_page&amp;btn-skin=2baf9e" loading="lazy"></iframe></p> <p>A three-year trial by fire at Tesla inspired Spencer Penn to start a software company to fix the problems he experienced with direct materials sourcing.</p> <p>Penn joined the electric vehicle maker in 2015, the year before it unveiled the Model 3, its first car designed to be affordable for middle-income buyers. His job focused on the financial aspects and business operations of engineering -- critical factors like labor costs and the car's bill of materials (<a href="https://www.techtarget.com/searcherp/definition/bill-of-materials-BoM">BOM</a>). Both had to support two big objectives: an ambitious, three-year development cycle -- half the usual turnaround time -- and a base price of $35,000.</p> <p>Penn found Tesla's sourcing process to be frustratingly manual, with fragmented BOMs and disconnected supplier workflows slowing product development and cutting into profit margins. He identified the cause as an automation gap between Tesla's product lifecycle management system, which was the engineering system of record, and its ERP, where financials were managed.</p> <p>Penn left Tesla in 2018, and in 2021 he cofounded LightSource to try to fill that workflow gap. The company makes an AI-native direct materials procurement "operating system" designed to integrate the entire design-to-production lifecycle and the workflow between engineers, buyers, suppliers and finance.</p> <p>In this episode of <i>Enterprise Apps Unpacked</i>, Penn gives examples of sourcing inefficiencies, explains their impact on the bottom line and shares what the Tesla experience taught him about how technology could solve complicated procurement problems.</p> <div class="imagecaption alignRight"> <img src="https://cdn.ttgtmedia.com/rms/onlineimages/penn_spencer.jpg" alt="Spencer Penn, LightSource CEO">Spencer Penn </div> <section class="section main-article-chapter" data-menu-title="Procurement at the center"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Procurement at the center</h2> <p>The compressed development schedule and low price point exerted tremendous pressure on Tesla employees, including Penn, who was helping engineering executives figure out how to source quality parts affordably and on time.</p> <p>"Tesla at that time was an all-you-can-eat buffet of pain points and problems, so I got exposed to everything. Procurement was just one of 20 things, but procurement was the one that to me felt so impactful because it directly hits the <a href="https://www.techtarget.com/searcherp/definition/profit-and-loss-statement-PL">P&amp;L</a> [profit and loss statement] of the business," he said. "There are two big flows of money in Tesla: in through the purchase of car parts, and out through the sale of delivered vehicles. Almost everything else is a rounding error."</p> <p>Many of the problems came from the sheer number of phone calls, emails and file exchanges needed to <a target="_blank" href="https://lightsource.ai/blog/sales-marketing-finance" rel="noopener">coordinate workflows</a> between engineering, finance, procurement, suppliers and manufacturing. The problems were magnified by Tesla's decision to run sourcing and product design in parallel, which was unusual&nbsp;at the time, according to Penn, but is now recognized as an innovation.</p> <p>"The car was being iterated at the same time that we were sharing drawings with suppliers, at the same time we were getting pricing and building out pilot and prototype lines," he said.</p> <p>The low point was what came to be known as the "production hell," when Tesla couldn't make all the cars it promised on time. Ultimately, the company took the lessons to heart, simplified its operations, and the Model 3 became the bestselling plug-in EV three years in a row.</p> <p>Other topics discussed in the podcast include the following:</p> <ul class="default-list"> <li>How LightSource works and who uses it.</li> <li>The "spec to scale" philosophy behind it.</li> <li>The role played by AI.</li> </ul> <p><i>David Essex is an industry editor who creates in-depth content on enterprise applications, emerging technology and market trends for several Informa TechTarget websites.</i></p> </section> In this podcast, LightSource CEO Spencer Penn explains how three years at Tesla motivated him to solve sourcing inefficiencies that kill margins and slow product development. https://cdn.ttgtmedia.com/visuals/digdeeper/6.jpg https://www.techtarget.com/searcherp/podcast/Direct-materials-sourcing-technology-a-hub-for-manufacturers Mon, 09 Mar 2026 05:00:00 GMT <p>Recruiting has become increasingly complex as organizations compete for skilled workers, manage hybrid workforces and adopt new HR technologies. To attract the right candidates and scale hiring effectively, organizations need a structured recruitment strategy and plan that aligns talent acquisition with business goals.</p> <p>To ensure that a company has an <a href="https://www.techtarget.com/searchhrsoftware/Ultimate-guide-to-recruitment-and-talent-acquisition">effective and efficient recruiting process</a> to find the right candidates, the talent acquisition team must develop a recruitment strategy and plan.</p> <section class="section main-article-chapter" data-menu-title="What is a recruitment strategy?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>What is a recruitment strategy?</h2> <p>A recruitment strategy is a long-term plan that defines how an organization attracts, sources and hires talent to meet business needs. It outlines hiring priorities, sourcing channels, the role of technology and how recruitment supports broader workforce planning. The strategy highlights how the company intends to recruit for open positions overall, when positions should be outsourced, the use of technology and <a href="https://www.techtarget.com/searchhrsoftware/definition/social-recruiting">social media</a>, and internal mobility. It might also include information about hiring a diverse workforce, employer branding and how open positions are prioritized.</p> <p>Then, a recruitment plan is developed that indicates how the strategy will be implemented. For example, the strategy might make internal hiring a priority. The recruitment plan identifies the specific steps, policies, program design, timelines and resources needed to make internal hiring a reality.</p> </section> <section class="section main-article-chapter" data-menu-title="Why is having a recruitment strategy important?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Why is having a recruitment strategy important?</h2> <p>The recruitment strategy helps the talent acquisition team know where to focus its attention, which is especially important when there are competing demands. The strategy also informs the HR team and managers about the big picture for recruitment and how the talent acquisition team is prepared to help the company meet its hiring needs.</p> </section> <section class="section main-article-chapter" data-menu-title="What should a recruitment plan include?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>What should a recruitment plan include?</h2> <p>A recruitment plan outlines how the company approaches the recruitment process and what recruitment tools are used in the short to medium term. Although the plan gets built after the recruitment strategy and is more specific, it still applies to all positions in the company that have to be recruited and isn't meant to provide details of each job requisition. Items that apply broadly to the recruitment function include the systems that are used, the vendors contracted to <a href="https://www.techtarget.com/searchhrsoftware/news/252514924/Employment-background-checks-shift-to-continuous">provide background checks</a>, how the company's website is configured to showcase open positions, the processes to follow during recruitment and where candidates are sourced from.</p> <p>The plan might include subplans for large groups of people with similar roles, such as industrial jobs that require certain steps to attract people in that industry, as opposed to office workers.</p> <p>The plan might also include budget information and workforce plans so that the talent acquisition team members can prepare for future hires.</p> <p>As talent acquisition works with hiring managers on new requisitions, they may develop specific hiring plans and strategies to fill each position, such as the tactics that may be used to source candidates for the position.</p> </section> <section class="section main-article-chapter" data-menu-title="What are the benefits of having a strong recruitment strategy and plan?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>What are the benefits of having a strong recruitment strategy and plan?</h2> <p>A well-planned recruitment strategy can do the following:</p> <ul class="default-list"> <li><b>Align recruitment efforts with company goals.</b> The recruitment strategy and associated plan help direct the work of the recruitment team by focusing on attracting and hiring people in the <a href="https://www.computerweekly.com/opinion/Where-are-all-the-technologists-Talent-shortages-and-what-to-do-about-them">areas most needed by the company</a> -- for example, looking for candidates in new locations in which the company plans to expand.</li> <li><b>Help establish a flexible budget for the plan.</b> A budget can be written to support the recruitment strategy and provide backup support if additional money is required -- for example, upgrading the process with a new applicant tracking system (<a href="https://www.techtarget.com/searchhrsoftware/definition/applicant-tracking-system-ATS">ATS</a>).</li> <li><b>Refine and improve hiring practices.</b> A repeatable process for attracting, <a href="https://www.theserverside.com/blog/Coffee-Talk-Java-News-Stories-and-Opinions/My-five-point-ranking-system-to-evaluate-tech-candidates">interviewing and rating candidates</a> can help identify top candidates more quickly, reduce bias and be adjusted over time.</li> <li><b>Save time.</b> A refined and uniform recruitment process identifies key components to ensure the right recruitment tools are in place for recruiters to use for every new job posting.</li> <li><b>Build and target a talent pipeline.</b> Recruiters better understand the areas of the company that are growing and the types of skills required, as well as <a href="https://www.techtarget.com/searchhrsoftware/feature/5-keys-to-a-killer-recruitment-marketing-strategy">select the most worthwhile networking events and sponsorships</a> that help build the targeted talent pipeline.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="How to define the goals of a recruitment plan"> <h2 class="section-title"><i class="icon" data-icon="1"></i>How to define the goals of a recruitment plan</h2> <p>For the talent acquisition team to validate that it is meeting the hiring needs of the company and hiring managers, the recruitment plan must include measurable goals. The goals should focus on activities that are in the control of the talent acquisition team. For example, time to hire is often used as a measure, but it can be affected by delays caused by people outside the talent acquisition team. Another example is the number of declined offers. Depending on the reason the candidate gave, such as the salary being too low, the metric might not be under the direct control of talent acquisition, but rather the hiring manager or finance department.</p> <p data-end="1515" data-start="1458"><strong data-end="1515" data-start="1458">Other useful metrics and goals include the following:</strong></p> <ul class="default-list"> <li data-end="1549" data-start="1519">Actual vs. budgeted expenses</li> <li data-end="1589" data-start="1552">Feedback on the recruitment process</li> <li data-end="1653" data-start="1592">Number of qualified candidates passed to the hiring manager</li> <li data-end="1703" data-start="1656">Number of leads gathered from networking events</li> </ul> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/hr_software-recruiting_strategy-f.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/hr_software-recruiting_strategy-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/hr_software-recruiting_strategy-f_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/hr_software-recruiting_strategy-f.png 1280w" alt="Illustration showing the steps involved in developing a recruitment strategy, including evaluating processes, recruiting tools and employer branding" height="286" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>Developing a recruitment strategy involves evaluating business goals, workforce needs, recruiting tools and employer branding. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> </section> <section class="section main-article-chapter" data-menu-title="Key elements of an effective recruitment strategy"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Key elements of an effective recruitment strategy</h2> <p>Formulating a recruitment strategy requires assessing current corporate processes, gathering feedback, implementing appropriate technologies, <a href="https://www.techtarget.com/searchhrsoftware/tip/10-HR-analytics-tools-that-can-optimize-your-workforce">evaluating workforce needs</a> and defining the employer brand and culture. The following steps outline the core elements of an effective recruitment strategy.</p> <h3>1. Assess current organizational strategies</h3> <p>Before developing a recruiting strategy, review existing corporate strategies that apply to recruiting, including the overall business strategy, current recruiting strategy and departmental strategies. Also, <a target="_blank" href="https://joshbersin.com/2024/05/enterprise-talent-intelligence-has-arrived-new-research-available/" rel="noopener">gather relevant information</a> from the company's workforce plan.</p> <p>These documents can provide key details, such as needed skills and corporate priorities, and validate compensation levels. The workforce plan might also include a calendar of key recruitment events to be held in busy times of the year -- for example, recruiting students in the summer or when there's a significant increase in the need for temporary workers.</p> <p>In addition, review departmental budgets for recruiting and various online platforms, like LinkedIn and Glassdoor, to search for ideal candidates.</p> <h3>2. Review strategy templates and best practices</h3> <p>Numerous recruitment strategy templates and best practice lists are available online. Review them to see what other companies are doing and what can be applied to the organization. Each organization is unique, however, and any best practice should be customized to fit the organization's brand.</p> <h3>3. Solicit feedback from stakeholders and candidates</h3> <p>Gather and incorporate stakeholder feedback from hiring managers, executives, employees and <a href="https://www.techtarget.com/searchhrsoftware/tip/Nine-different-HR-roles-and-responsibilities-demystified">HR teams</a>, as well as job candidates.</p> <h3>4. Implement advanced tools and technologies</h3> <p>Small companies might rely on a manual process, but specialized software is often necessary as the recruitment volume increases. There are many options to consider when it comes to recruitment applications. An <a href="https://www.techtarget.com/searchhrsoftware/feature/HRIS-vs-HRMS-vs-HCM-Key-differences-and-similarities">HR management system</a> often includes a recruitment module with basic functionality to automate recruiting processes. In addition, some vendors specialize in developing ATSes that offer more advanced functionality. Consider the following technologies:</p> <ul class="default-list"> <li><a href="https://www.techtarget.com/searchhrsoftware/tip/6-ways-AI-can-improve-the-talent-acquisition-process">AI tools can help target potential candidates</a> with job ads, prescreen and rank resumes for review, assist with <a href="https://www.theserverside.com/blog/Coffee-Talk-Java-News-Stories-and-Opinions/Four-interviewing-techniques-to-evaluate-a-tech-hire">interviews and measure candidate responses</a>. Increasingly, organizations also use AI tools to automate candidate communication, screen applicants at scale and improve recruiter productivity. <a href="https://www.techtarget.com/searchhrsoftware/tip/Pros-and-cons-of-an-applicant-tracking-system">ATSes can also</a> use AI to build a more comprehensive view of candidates by pulling data from social media and websites.</li> <li>Resume-parsing tools automatically read resumes submitted by candidates and place the data in the right fields in the recruiting system -- for example, they put the education information on a resume in the ATS' education field. At the start of the hiring process, this capability can eliminate the need to open each resume individually and enables keyword searches across all candidates.</li> <li><a href="https://www.techtarget.com/searchhrsoftware/definition/video-interview">Video interviewing</a> software can be standalone or part of the ATS. It eliminates the need for in-person interviews, facilitates team interviews and makes it possible to interview qualified candidates face to face, regardless of their location.</li> <li>Job boards at sites like LinkedIn and Glassdoor expand an organization's search capabilities. Since they often cost money, it's important to capture and analyze where applicants are finding job postings to determine, for example, which job boards are geared toward permanent professional positions and which are better for attracting temporary help.</li> <li><a href="https://www.techtarget.com/searchhrsoftware/feature/What-types-of-technologies-help-with-remote-onboarding">Onboarding is an extension of the recruiting process</a> and can improve a new hire's overall experience with the organization. Adding an onboarding module to the HR system or ATS automates the distribution and signing of policies and forms. It also <a href="https://www.techtarget.com/searchhrsoftware/feature/How-to-welcome-a-new-employee-virtually-and-boost-retention">helps new employees learn about the company</a>.</li> </ul> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/hr_software-applicant_tracking_system-f.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/hr_software-applicant_tracking_system-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/hr_software-applicant_tracking_system-f_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/hr_software-applicant_tracking_system-f.png 1280w" alt="Diagram showing key functions of an applicant tracking system, including job postings, candidate applications, interviews and onboarding." height="584" width="559"> <figcaption> <i class="icon pictures" data-icon="z"></i>An applicant tracking system (ATS) helps organizations manage job postings, candidate applications, interviews and onboarding. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <h3>5. Examine HR policies and practices for employees</h3> <p>The company's policies and practices concerning benefits, vacation policies, corporate social responsibility, professional development and <a href="https://www.techtarget.com/searchhrsoftware/feature/8-workforce-management-tools-to-support-flexible-work-hours">flexible work options can provide an edge</a> when competing for top talent.</p> <p>Also, examine the interview process itself -- for example, whether phone screening is used for the first interview or if interview teams handle all positions or only those above a certain level. Take a look, too, at the timing and types of background checks to be conducted and by whom. This review of the hiring process might reveal outdated policies that are turning off candidates.</p> <h3>6. Identify ways to attract job candidates</h3> <p>Many methods are available to <a href="https://www.techtarget.com/searchhrsoftware/feature/How-are-recruitment-and-talent-acquisition-different">increase the talent pipeline</a> and attract both active and passive job seekers. Prepare a communication channel to identify the ideal forums for a particular open role, create an <a href="https://www.techtarget.com/searchhrsoftware/feature/20-social-media-recruiting-strategies-that-work">engaging social media campaign that attracts candidates</a> and validate effectiveness with metrics. What works for one role may be entirely different for another.</p> <p>Posting open positions on the company website gives candidates a degree of familiarity with the corporate culture and what it has to offer. Other options include posting to job boards, offering an employee referral program, contacting past employees, manually searching for <a href="https://www.techtarget.com/searchhrsoftware/definition/passive-candidate">passive candidates</a>, reviewing existing talent pools in the ATS, outsourcing to a third party and hosting internal business events. Posting open positions in specific locations, such as organization sites that help those in underrepresented communities find employment opportunities, can help attract diverse candidates.</p> <p>Also, consider advertising open roles. When using job boards, decide whether the advertisement applies to all job postings or only those in a certain category, and determine whether to allow candidates to text their applications for roles that typically have high turnover rates. In addition, consider whether to market open positions. Determine, for example, whether to use video to make postings more attractive to candidates or develop a more sophisticated template to market open positions instead of simply posting job descriptions.</p> <h3>7. Evaluate the current recruitment process</h3> <p>Regularly evaluating the company's recruitment process ensures the program's practices and procedures remain effective. It's also critical to consider the process in terms of the candidate experience. The recruitment team should walk through <a href="https://www.techtarget.com/whatis/feature/9-best-practices-for-a-positive-candidate-experience">all the steps a candidate might take</a> when considering a position in the organization. Seek feedback from candidates and hiring managers in the spirit of continuous improvement.</p> <div class="youtube-iframe-container"> <iframe id="ytplayer-0" src="https://www.youtube.com/embed/tBaq3J2-AHk?autoplay=0&amp;modestbranding=1&amp;rel=0&amp;widget_referrer=null&amp;enablejsapi=1&amp;origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0"></iframe> </div> <h3>8. Differentiate employee and contingent workforces</h3> <p>Depending on an organization's business requirements, an HR recruiting strategy may also have to take into account whether the talent search specifies permanent employees or <a href="https://www.techtarget.com/searchcio/definition/contingent-workforce">contingent workers</a>. Consider enlisting a third-party search agency to <a href="https://www.techtarget.com/searchhrsoftware/tip/6-best-practices-for-managing-a-contingent-workforce">recruit contingent workers</a> since they often can draw from an existing pool of talent.</p> <p>Another consideration is whether the company develops employees internally to fill future vacancies or hires candidates externally. Both approaches have advantages and disadvantages, including the following:</p> <ul class="default-list"> <li>Existing employees are a known quantity. Skills, abilities and work ethic can be readily evaluated in an employee's current role, but extensive training might be needed to step into a new position outside their area of expertise.</li> <li>External candidates hired for specific skill sets can step into a position with little or no downtime but may not adapt to the company's culture, and their hiring might discourage current employees from seeking new opportunities in the organization.</li> </ul> <h3>9. Consider outsourcing to recruitment agencies</h3> <p>There are many outsourcing options for recruiting. The company's internal talent acquisition team can handle the day-to-day recruitment process, but consider partnering with a third-party agency for special recruiting situations. It may be more expedient and cost-effective, for example, to hire specialized recruitment agencies to handle a one-time need for a large number of workers with the same skill sets. Another scenario might be to build long-term partnerships with third-party recruiters, regardless of circumstance, while retaining some recruitment in-house.</p> <h3>10. Define and refine the company's brand</h3> <p data-end="2511" data-start="2297">An employer's brand can significantly influence the quantity and quality of candidates for open positions, as well as employee perceptions of the company. A strong brand can be a big help in the recruiting process.</p> <p data-end="2773" data-start="2513">Defining and refining a brand that's not well known should be an important component of a company's overall marketing and recruiting strategies. Organizations can also use company review platforms, such as Glassdoor, to monitor and improve employer reputation.</p> <div class="extra-info"> <div class="extra-info-inner"> <h3 class="splash-heading">Core elements of a successful recruitment strategy:</h3> <ul class="default-list"> <li data-end="2130" data-start="2096">Align hiring with business goals</li> <li data-end="2174" data-start="2133">Use technology to streamline recruiting</li> <li data-end="2208" data-start="2177">Build a strong employer brand</li> <li data-end="2247" data-start="2211">Expand candidate sourcing channels</li> <li data-end="2295" data-start="2250">Continuously evaluate recruitment processes</li> </ul> </div> </div> </section> <section class="section main-article-chapter" data-menu-title="Stepping up recruiting efforts"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Stepping up recruiting efforts</h2> <p>Recruiting the right people at the right time remains a critical priority for organizations <a href="https://www.techtarget.com/searchhrsoftware/feature/7-talent-acquisition-strategies-for-better-hiring-in-2023">competing for skilled talent</a> and managing hybrid and remote workforces. A structured recruitment strategy helps talent acquisition teams align hiring with business goals, improve the candidate experience and build a sustainable talent pipeline.</p> <p><em>Eric St-Jean is an independent consultant with a particular focus on HR technology, project management and Microsoft Excel training and automation. He writes about numerous business and technology areas.</em></p> </section> A strong recruitment strategy helps organizations attract the right candidates. Learn 10 steps to evaluate policies, use recruiting technology and strengthen employer branding. https://cdn.ttgtmedia.com/rms/onlineimages/strategy_a296343799.jpg https://www.techtarget.com/searchhrsoftware/tip/10-steps-for-developing-a-recruiting-strategy Thu, 05 Mar 2026 09:44:00 GMT <p>As with any software, people are needed to manage it -- and ERP software is no exception.</p> <p>CIOs and any other C-suite leaders who work with ERP software should ensure that those who hire employees to work with ERP software are checking for some specific skills before bringing new people on board.</p> <p>ERP systems are complex, as they manage numerous business requirements while also needing integrations with other systems. These complexities require organizations that deploy their own ERP systems to also employ an ERP professional to handle the system. An ERP professional's role typically includes the following tasks:</p> <ul class="default-list"> <li>Keeping projects on track.</li> <li>Implementing and updating the ERP system.</li> <li>Driving <a href="https://www.techtarget.com/searchcio/definition/change-management">change management</a> initiatives.</li> <li>Aiding budget expectations.</li> <li>Educating users.</li> <li>Helping shape user experiences.</li> </ul> <p>Successful ERP professionals must possess a varied skill set that demonstrates both the hard and soft skills needed to run and manage an ERP system.&nbsp;</p> <div class="youtube-iframe-container"> <iframe id="ytplayer-0" src="https://www.youtube.com/embed/PPewd17otM0?autoplay=0&amp;modestbranding=1&amp;rel=0&amp;widget_referrer=null&amp;enablejsapi=1&amp;origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0"></iframe> </div> <section class="section main-article-chapter" data-menu-title="ERP skills"> <h2 class="section-title"><i class="icon" data-icon="1"></i>ERP skills</h2> <p>The following 10 hard and soft skills are must-haves for any employee who will be implementing and managing an ERP system.</p> <h3>1. Intuition</h3> <p>Intuition is one trait that can't be trained or taught. Instead, it's either innate, or it takes years of experience in project management to build up. ERP project managers should have the ability to sense how a project is developing and should have an instinct built for detecting issues.</p> <h3>2. Project management</h3> <p>A CIO's company is likely looking for candidates who have been responsible for a project before and have had experience working with a full ERP implementation lifecycle. ERP professionals should have <a href="https://www.techtarget.com/searchcio/definition/project-management">project management</a> skills, including project planning and execution. They should also have skills in managing multiple projects, timelines and budgets.</p> <h3>3. Problem-solving</h3> <p>A company's ERP implementation should go smoothly, and their ERP professional should be able to fix any problems that occur. An ERP professional should be able to identify, analyze, troubleshoot and remedy any technical issues that arise. Past examples of such problem-solving skills can also be useful.</p> <h3>4. Resourcefulness</h3> <p>An ERP professional should be able to pinpoint ERP processes and configurations that can be improved. A level of resourcefulness is needed to create a strategy to make modifications or updates to the ERP implementation that also maximizes return on investments and productivity. A CIO's company is likely looking for resourceful candidates who can solve the organization's problems with the resources they have on hand.</p> <h3>5. Up to date with technology</h3> <p>ERP professionals should have experience in or knowledge of using the proper technologies to implement and manage ERP hardware and software. Skills in ERP technologies can be gained from firsthand experience, training or certification programs. The technologies, technical skills and experiences ERP professionals should possess include the following:</p> <ul class="default-list"> <li>Artificial intelligence.</li> <li>Big data.</li> <li>Creating custom reports.</li> <li>Data management.</li> <li>Data integration.</li> <li>Data migration.</li> <li>Data modeling.</li> <li>Predictive analytics.</li> <li>Programming languages such as <a href="https://www.techtarget.com/searchdatamanagement/definition/SQL">SQL</a> or <a href="https://www.techtarget.com/whatis/definition/XML-Extensible-Markup-Language">XML</a>.</li> <li><a href="https://www.techtarget.com/searchcio/definition/RPA">Robotic process automation</a>.</li> </ul> <p>ERP professionals should also have some familiarity with ERP systems and architectures -- such as those from <a href="https://www.techtarget.com/searchsap/definition/SAP">SAP</a>, Microsoft and Oracle -- as well as any local data standards and regulations.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/2023_top_manufacturing_erp_systems-f.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/2023_top_manufacturing_erp_systems-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/2023_top_manufacturing_erp_systems-f_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/2023_top_manufacturing_erp_systems-f.png 1280w" alt="Top manufacturing ERP systems for 2023." height="493" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>ERP professionals should have some familiarity of different ERP systems and architectures, including those from vendors such as Microsoft, SAP and Oracle. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <p>ERP systems also differ from vendor to vendor, which means the more well-versed a candidate's skills are, the better.</p> <h3>6. Effective communication</h3> <p>Leading an ERP implementation requires good communication skills. ERP professionals should be able to openly discuss projects with their teammates in a clear and concise manner. The ability to communicate clearly -- through spoken or written word -- is an integral part of making a project plan succeed.</p> <p>Organizations also value the ability to resolve conflicts and disagreements between team members in a calm and reasonable manner.</p> <h3>7. Mentoring</h3> <p>Another valued skill for ERP professionals is the ability to teach skills to other employees. ERP professionals who feel comfortable sharing their knowledge while also being able to learn from their peers strengthen those individuals' skills -- while also strengthening the skills of their team.</p> <p>An ERP professional providing mentoring and support to those around them also helps keep a project on track by saving time on training and lets organizations retain employees who might lack specific skills.</p> <h3>8. Team building</h3> <p>The ability to bring a team together is a soft skill ERP project managers must possess. ERP professionals should be able to provide feedback to their teams, guide them when needed and give them opportunities to try new things while also knowing what is expected from them.</p> <p>Teams should be able to come together to collaborate, share knowledge and solve any potential technical issues. It is also important for ERP professionals to develop their conflict resolution skills to prevent any fights or tensions between team members.</p> <h3>9. Flexibility</h3> <p>ERP systems are designed with flexibility and scalability in mind -- with the idea that they can be customized over time to meet the changing needs of an organization. Likewise, ERP professionals should be flexible and adaptable to new changes and unexpected conditions.</p> <p>The process of implementing an ERP system is typically complex, and there might be problems along the way. The ability for ERP professionals to stay calm and flexible throughout the project is integral. They should stay open to feedback while also being able to make changes to project plans as needed.</p> <h3>10. Organization</h3> <p>There are many parts of an ERP project that need some level of organization -- including the organization of the ERP project plan and the people involved in developing it.</p> <p>Different aspects of an ERP project that require organization include the following:</p> <ul class="default-list"> <li>Contracts.</li> <li>Documentation.</li> <li>Emails.</li> <li>Lists of employee tasks.</li> <li>Memos.</li> <li>Project requirements and specifications.</li> <li>Reports.</li> <li>Reviews.</li> <li>Risks.</li> </ul> <p>Organizations will benefit from an ERP professional's ability to be organized. Time management is also an essential ERP skill, as it's difficult to stay organized without being able to manage time accurately.</p> <p><i>Alexander Gillis is a technical writer for the WhatIs team at TechTarget.</i></p> </section> Both hard and soft skills are essential for ERP professionals, including project management and being up to date with technology. https://cdn.ttgtmedia.com/rms/onlineimages/check_g1199243271.jpg https://www.techtarget.com/searcherp/feature/Essential-skills-for-ERP-professionals Wed, 25 Feb 2026 14:00:00 GMT <p><iframe title="Capgemini exec shares lessons from SAP agentic AI projects" allowtransparency="true" height="150" width="100%" style="border: none; min-width: min(100%, 430px); height: 150px;" scrolling="no" data-name="pb-iframe-player" src="https://www.podbean.com/player-v2/?i=fc8uv-1a4fd92-pb&amp;from=pb6admin&amp;pbad=0&amp;share=1&amp;download=1&amp;rtl=0&amp;fonts=Arial&amp;skin=1&amp;font-color=auto&amp;logo_link=episode_page&amp;btn-skin=2baf9e" loading="lazy"></iframe></p> <p>Agentic AI is the hottest trend in ERP as vendors race to offer special-purpose AI agents, development tools for building custom agents and new data products expressly designed for AI.</p> <p>SAP, along with ERP archrival Oracle, is leading this AI push, especially since the debut of generative AI (<a href="https://www.techtarget.com/searchenterpriseai/definition/generative-AI">GenAI</a>) three years ago. Building on earlier machine learning technology, it first added a GenAI copilot called Joule, later augmenting it with the decision-making and autonomy that define agentic AI. It then added Business Data Cloud for the <a href="https://www.techtarget.com/searchsap/news/366633925/At-TechEd-SAP-continues-to-lay-down-the-AI-data-foundation">cross-platform data integration</a> AI needs to be effective.</p> <p>The promise is AI that can anticipate users' needs, communicate with them in their native language and handle many of the tasks that otherwise require tedious data entry and switching between ERP screens.</p> <p>But building agentic AI that works across SAP and non-SAP systems isn't easy. In this episode of <i>Enterprise Apps Unpacked</i>, Gianluca Simeone, vice president and chief technology and innovation officer at Capgemini, the French multinational IT services firm, shares lessons learned from practical experience, including the design process, development tools and challenges of integrating SAP AI agents as well as orchestrating their behavior.</p> <div class="imagecaption alignRight"> <img src="https://cdn.ttgtmedia.com/rms/onlineimages/simeone_gianluca.jpg" alt="Gianluca Simeone, vice president and chief technology &amp; innovation officer, Capgemini">Gianluca Simeone </div> <section class="section main-article-chapter" data-menu-title="Agents of change"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Agents of change</h2> <p>Based in Milan, Italy, Simeone has more than 20 years of development experience on SAP platforms. He joined Capgemini in 2013 as an SAP enterprise architect and later worked on development teams focusing on major cloud platforms, including AWS, Google Cloud and Microsoft Azure. In recent years, his focus has been SAP AI projects.</p> <p>In one case, Simeone's team <a target="_blank" href="https://www.sap.com/assetdetail/2025/10/8436afc5-287f-0010-bca6-c68f7e60039b.html" rel="noopener">reportedly</a> took just three weeks to use Joule Studio to develop custom agents that work across SAP and non-SAP systems to automate the <a href="https://www.techtarget.com/searcherp/definition/procure-to-pay-P2P">procure-to-pay</a> process of an oil and gas company.</p> <p>He said multi-agent orchestration, where agents from different vendors and platforms work together, is still under development as the industry works on protocols and standards. For example, Capgemini has a three-way partnership with SAP and Google to use the latter's <a href="https://www.techtarget.com/searchenterpriseai/news/366622027/Google-intros-tools-for-building-agents-and-a-new-protocol">Agent2Agent Protocol</a>, enabling agents from both vendors to consume data and communicate with each other. They're experimental now but could be offered to Capgemini clients in a few weeks, Simeone said.</p> <p>"The real value from agent-to-agent will come when we have SAP offering a list of agents to execute specific tasks and other players, like the hyperscalers or other vendors, releasing something similar, and having Capgemini as a system integrator working with our clients to connect the dots between the multiple agents to orchestrate end-to-end business processes," he said.</p> <p>Other topics discussed in the podcast include the following:</p> <ul class="default-list"> <li>Whether nontechnical business leaders are using <a href="https://www.techtarget.com/searchsoftwarequality/definition/low-code-no-code-development-platform">low-code and no-code development tools</a> to play a meaningful role in building agents.</li> <li>The integration tools and standards used in the SAP agentic AI projects.</li> <li>What makes agentic AI projects successful.</li> </ul> <p><i>David Essex is an industry editor who creates in-depth content on enterprise applications, emerging technology and market trends for several Informa TechTarget websites.</i></p> </section> In this podcast, Capgemini VP Gianluca Simeone explains how it's possible to build useful, cross-platform agentic AI applications in weeks, despite a lack of industry standards. https://cdn.ttgtmedia.com/visuals/digdeeper/2.jpg https://www.techtarget.com/searcherp/podcast/Capgemini-exec-shares-lessons-from-SAP-agentic-AI-projects Mon, 23 Feb 2026 05:00:00 GMT 60 webmaster@techtarget.com