Abhishek Jha’s Post

💡 Business Model Innovation in the AI Era Bessemer Venture Partners’ latest article explores how AI is driving business model innovation, with a focus on AI-enabled services. This shift is unlocking new ways for companies to deliver value, optimize operations, and create scalable revenue streams in the age of artificial intelligence. At Zenith Venture Studio, we’re witnessing how B2B AI SaaS startups are leveraging these innovative models to disrupt traditional industries and redefine value creation. Read the full article here 👉 https://lnkd.in/gQm-Bg4a #AIBusinessModels #B2BAISaaS #ArtificialIntelligence #Innovation #VentureStudios

Business model innovation is the backbone of success for B2B AI SaaS startups! 💡 This post dives into how inventive approaches to monetization can drive both growth and sustainability. As someone deeply invested in this space, I’ve seen firsthand how the right model can unlock exponential value. 🚀 #BusinessModelInnovation #B2B #SaaS #AI #StartupGrowth #VentureStudio #TechLeadership #Innovation

2024 Google Cloud Next event begins today. It is the right time to get best practices sharing from Uber, Etsy, Bayer, HCA Healthcare, Verizon, Walmart, Mercedes-Benz... About Startups, we share few numbers: more than 60% of funded generative AI startups, and nearly 90% of gen AI unicorns are Google Cloud customers. Why this position? Our deep investments in AI for a long time with a long term vision... #AI is going to drive incredible opportunities including to make AI helpful for everyone, and to improve the lives of as many people as possible; Google's mission! Ready to join us in the livestream now?

Can AI agents overcome the challenges of scaling SaaS from Southeast Asia? Microsoft's Satya Nadella ended his 2024 preaching "AI agents will replace all software" He put into words a conviction Microsoft and its big tech peers investing roughly US$200B are racing to materialize. On the supply side, Y Combinator's F24 batch out of the 96 companies in the batch, 80 are tagged AI/ML with around 45 companies or half of the cohort either Agentic AI focused or related to Agentic AI. From both the potential acquirers and startups being built, a pipeline is developing around agentic AI companies to be venture-backed and find meaningful exits in this decade. But there's one problem. This is mostly a US / Silicon Valley pipeline (73 out of the 96 YC startups come from North America in that same cohort) What is the reality of AI agents replacing software? We tackle this question by diving into what makes agentic AI different: 1️⃣ from generative AI ➡️ not just RAG 2️⃣ from software in an adoption perspective ➡️ lower implementation costs 3️⃣ from software in a Southeast Asia socio-economic perspective ➡️ competing with big tech, low labor costs, and bottom up pushback then tackling considerations for founders in the region when it comes to developing and selling AI agents: 👉 SaaS companies in the region have traditionally faced customer acquisition and revenue growth challenges in markets apart from Singapore. 👉 This has led to a number of SEA-based SaaS companies to either find early exits in global acquirers or... 👉 ...rapidly expanding their target customer pool to tier 1 markets in east Asia and even across the Pacific to balance out the margins of operating in Southeast Asia. Does agentic AI have the potential to find more meaningful adoption in Southeast Asia? Is it a matter of time or is the competitive landscape maturing faster than adoption trends can adjust? Read the full article on Insignia Business Review in the comments 👇

Interesting "dualism" between #SaaS solutions and #Ai #GenerativeAi quoted in this article of PitchBook : " revenue figures indicate that AI experimentation may be diverting corporate dollars away from SaaS" ( see interesting graph of average growth of SaaS companies in the last years) In reality, a statement of evident future context: all #SaaSB2Bsolutions that will have a future ARE already fully #Ai so the duality of "more AI less other SaaS" does not exist because #AIisSaas in the future The big next step is #Generativeai for Corporate and the SaaS or "non SaaS" ( Open Source) implementation" of genai solutions within corporate with their processes and in their data Rosie Bradbury iGenius https://lnkd.in/dYS-bc_j

🚀 Harnessing AI for Tangible Results: A Real-World Use Case Want to see how AI is transforming marketing operations? Join us as Thomas Van der Staaij shares how Amazon Web Services (AWS) global campaign managers have leveraged generative AI to: ✅ Cut campaign timelines from months to weeks ✅ Streamline workflows and reduce costs ✅ Boost productivity without sacrificing quality This session will dive into real-world examples of AI’s impact, from creating content and ads to executing end-to-end campaigns more efficiently—all while maintaining realistic expectations. You’ll also gain insights into: 👉 Overcoming adoption challenges 👉 Scaling AI across teams 👉 Addressing the culture shifts that come with rapid AI evolution Walk away with actionable strategies to implement AI and achieve meaningful results for your organisation. Sound interesting? Register today to save £300 off your ticket: https://lnkd.in/ecdrfqhQ Don’t miss it! Our early bird offer ends in just a few days ( 31 Jan) so be quick! 📅29-30 April 2025 📍Hilton London Tower Bridge #HyperGrowthMarketing #B2BMarketing #Scaleups #Startup #GenAIMarketing #AWS #B2BScaleup #B2BStartup #StartupEcosystem

Stripe analyzed data from its 100 fastest-growing AI customers and compared their revenue growth to 100 top SaaS companies from 2018, marking the start of the SaaS era. Notable AI customers include Anthropic, OpenAI, and Midjourney. The data reveals that AI startups reach $1M in annualized revenue in a median of 11 months, compared to 15 months for SaaS companies. Furthermore, AI startups scale from $1M to $30M at five times the rate of SaaS companies, indicating exceptionally rapid growth. However, this fast growth comes with unique challenges. AI companies face high initial compute costs that put pressure on them to monetize quickly. As Emily Sands from Stripe noted, “AI companies pay substantial compute costs out of the gates, so are under pressure to build monetization faster.” The differences in business models are significant. AI companies often charge based on usage (per task, per API call), whereas SaaS companies traditionally rely on subscription fees. Additionally, AI companies focus heavily on data acquisition, model training, and algorithm refinement to improve product value, while early SaaS companies prioritized optimizing user experience and customer retention. These factors highlight the distinct challenges and growth opportunities facing AI startups. While their revenue growth is remarkable, the pressure to scale rapidly and manage high upfront costs presents unique obstacles that must be navigated to sustain long-term success. Geeks Of The Valley Roshan Mirajkar Kunal T. https://lnkd.in/gXfjxVYr

I often get the question why there's a need for Maya Travel - as in why existing (horizontal) solutions aren't good enough. After reading the NFX article on Verticalization - I realize the answer is "they might be good, but not great" and in the AI era that results in the difference between "a tool that helps" and fully replacing some processes end-to-end. Great read by NFX: https://lnkd.in/eWDcgjkT . "Delivering “great” is where a startup can begin to gain ground among many “good” legacy options. ... Furthermore, the market for these companies is not the existing SaaS markets, but the cost of doing the entire work itself, a market we believe to be at least an order of magnitude greater. Previously ignored niches are becoming multi-billion dollar opportunities."

“This time it’s different.” The four most dangerous words in the English language - but is genAI the exception that proves the rule? According to the FT “AI start-ups that have scaled to more than $30mn in annualised revenue achieved the milestone in 20 months — five times faster than past SaaS companies.” I certainly know genAI startups that aren’t getting such strong traction, often because their potential customer base hasn’t yet moved into an AI-first mindset, allocated budgets and prioritized work beyond pilots. But with the HBR study showing that on many measures AI can outperform human CEOs, I feel we might be about to see a shift. How about you? How many AI SaaS products are you subscribing to? How many hours of your day are AI-powered?

From AI agents to enterprise budgets, 20 VCs share their predictions on enterprise tech in 2025 | AI adoption by enterprises, didn’t play out in 2024 as budgets remained constrained and AI tech often remained in the “experimental” category | TechCrunch https://buff.ly/4fF0IfS