World Data Summit

What’s stopping great ideas from becoming real data outcomes? At the World Data Summit 2025, Kamran Ashraf made one thing clear: data success depends just as much on organisational alignment as on technology. He shared what teams must get right to translate insights into real results. Kamran outlined three critical priorities: 1️⃣ A deep understanding of the business objectives behind every use case, 2️⃣ Strong #dataarchitecture and systems that make your #data usable and available, 3️⃣ Robust #datagovernance and #privacy frameworks to ensure responsible, secure data use. Looking ahead, Kamran sees the next 3–5 years as the time to get serious about #artificialintelligence as an assistant. By automating low-value tasks, #AI can free up #dataprofessionals to focus on strategy, critical pain points, and areas where human insight is most valuable. What makes the Summit unique, Kamran shared, is the thoughtfulness behind the experience: from carefully chosen speakers to space for deep, honest conversations. Real lessons, real challenges, and collaboration across business, #tech, cyber, and legal - that’s where meaningful progress takes shape. 💡 Watch the full interview below to hear why aligning teams and rethinking collaboration may be the biggest data shift yet. What’s been your biggest challenge in turning shared data goals into shared action? Let us know in the comments. #worlddatasummit #WDS2025 #datamanagement #dataengineering #datainnovation #bigdata #datascience #dataprivacy #dataanalytics

IBM’s 2025 Cost of a #DataBreach Report revealed a sharp gap between rapid #AI adoption and the oversight needed to secure it. Although the global average data breach cost fell slightly to $4.44 million, security incidents involving AI systems remain more severe and disruptive. Around 13% of organisations reported breaches involving AI models or applications, while 8% were unsure whether they had been compromised. Alarmingly, nearly all AI-related breaches occurred without access controls, leading to #dataleaks in 60% of cases and operational disruption in almost one-third. #ShadowAI played a central role, with one in five breaches traced back to it. Organisations without AI governance policies or detection systems faced significantly higher costs, especially when PII or intellectual property was exposed. Attackers increasingly used AI tools such as deepfakes and phishing, with 16% of studied breaches involving AI-assisted threats. Healthcare remained the costliest sector, with an average breach price of $7.42 million and the most extended recovery timeline of 279 days. Despite the risks, fewer organisations plan to invest in post-breach security. Only 49% intend to strengthen defences, down from 63% last year. https://lnkd.in/d5RRb2cg #worlddatasummit #datagovernance #data #datasecurity #dataanalytics

The #DataProtection Commission has launched a new Adult Safeguarding Toolkit to provide organisations and individuals with guidance and resources to protect the personal data of vulnerable adults. This initiative aims to ensure #compliance with data protection legislation and promote best practices in safeguarding sensitive information. The toolkit offers comprehensive guidance on how to collect, use, store, and share #data related to vulnerable adults, while adhering to the principles of the #GDPR and the Data Protection Act 2018. It includes practical advice, templates, and examples to help organisations implement effective data protection measures. https://lnkd.in/et7bXKjn https://lnkd.in/eCz4PMqm #worlddatasummit #customeranalytics #businessanalytics #datascience

India is poised for the world’s largest workforce transformation, with #agenticAI expected to redefine 10.35 million roles by 2030, according to newly released AI Skills Research 2025.  This shift signals an opportunity for India’s talent base, shifting from process-driven tasks to purpose-led innovation. The research highlights a range of role evolution: ✔️ High-automation roles like change managers and payroll clerks are changing, with #AIagents taking over routine coordination. ✔️ High-augmentation roles such as implementation consultants and system admins are increasingly partnering with #AI. ✔️ Manufacturing (8 million), retail (7.6 million), and education (2.5 million) sectors will bear the highest impact of this transformation. ✔️ With the world’s largest youth population and a dynamic digital economy, India is poised to add three million tech workers over the next five years. Enterprises are prioritising roles such as AI configurators (66%), experience designers (57%), and #datascientists (65%), as per research, and 13.5% of tech budgets are already committed to AI adoption. Almost 25% of Indian enterprises are in the transformation phase, outpacing markets like Singapore (20%) and Australia (21%). #Datasecurity tops the list of concerns for 30% of Indian enterprises, the highest in the region. Additionally, 26% of organisations remain unclear about the future skillsets required. Read more at: https://lnkd.in/dgpj73_k #worlddatasummit #dataquality #dataengineering #dataarchitecture #ml #machinelearning #datascience #bigdata #datainnovation #dataanalytics

A new survey has indicated that a significant majority of #APAC retailers remain confident in executing their customer engagement strategies over the coming 12 months, despite an environment of increasing economic uncertainty. Four in five APAC retailers feel assured in their ability to successfully implement their customer engagement plans for the year ahead. The findings are anchored in input from 288 retail professionals spread across the region. This confidence persists even as 43% of respondents anticipate both opportunities and challenges in the current market landscape. The report reveals that maintaining customer trust and loyalty is cited as the top concern by 27% of those surveyed, with price-related dissatisfaction (23%) and managing communications on pricing and product availability (21%) trailing close behind. In response to these challenges, many APAC retailers are renewing their focus on loyalty and re-engagement initiatives to reinforce their relationships with customers. Nearly 28% of survey participants identified this area as their most significant untapped opportunity. Product discovery (24%) and post-sale care (18%) were also highlighted as important focal points for investment and improvement within the customer journey. Retailers are increasingly prioritising tools intended to enhance personalised engagement. Around 25% reported investment in personalised offers and loyalty schemes, 27% in conversational #artificialintelligence, and 22% in additional human agent support. These shifts reflect a broader dedication across the sector toward delivering targeted, empathetic, and human-centred experiences for customers at all stages of interaction. https://lnkd.in/eFQiWAX7 #worlddatasummit #customeranalytics #businessanalytics #datascience #CXanalytics #AI #dataanalytics #datastrategy #dataanalysis #bigdata

Cross-border #dataregulations have turned privacy into a boardroom-level concern. With the right foundation, built on visibility, flexibility and shared responsibility, privacy #compliance can become a business advantage. The key is to proactively address the challenge rather than react to individual regulations in isolation. This approach is not only more sustainable but also creates space for innovation, customer trust and operational efficiency. #Privacy doesn’t belong to one team – make privacy a shared goal across legal, #IT, product, marketing and operations. That starts with assigning clear responsibilities.  Each function has its role to play: engineering enforces technical safeguards, marketing ensures transparent messaging and product teams design with consent and data minimization in mind. Embedding privacy leads within key teams ensures issues are raised and addressed early. Cross-functional steering committees provide a forum for alignment and escalation. These groups track progress on strategic privacy goals, surface real-time concerns and ensure that decisions are actionable.  Shared key performance indicators and incentives tied to trust and #data safety mean privacy is baked into daily workflows, not tacked on at the end. Don’t wait for new laws to force action. Get ahead of them. Build privacy into your foundation. Make it strategic, collaborative and consistent. When you do, privacy becomes both a strength and a mandate. https://lnkd.in/ddxamim8 #worlddatasummit #businessanalytics #dataprotection #dataanalytics

The IBM commissioned study, #APAC #AIDriven Industry 4.0: Building Tomorrow’s Industries, reveals that manufacturing, energy and utility organisations in the Asia Pacific region are investing heavily in #AI and Industry 4.0 capabilities, but many overestimate their actual readiness and struggle with fundamental challenges in holistic adoption. Key barriers include: ❗Strategic misalignment: Only 10% of organisations have a fully embedded Industry 4.0 strategy, while 70% have strategies without execution, siloed plans, or isolated pilots, risking fragmented and ineffective progress. ❗People and adoption blind spots: 19% worry about employee resistance, and only 26% run formal upskilling or change-management programs, leaving only 16% confident in their in-house expertise. ❗ Siloed execution: Around 67% pursue ad hoc, department-level use cases, and 73% lack mechanisms for cross-team knowledge sharing, hampering collaboration and innovation. ❗ Slow core modernisation: Only 40% have broadly adopted predictive maintenance, and just 37% enjoy real-time supply-chain visibility, exposing organisations to downtime and disruptions. ❗ Limited AI integration: Although 63% focus AI on isolated processes, only 10% treat AI/ #ML as a strategic pillar, leaving end-to-end, intelligent operations largely unrealised. Looking ahead, the transition from Industry 4.0 to Industry 5.0 - where human-centricity, sustainability, and resilience become core - remains a major hurdle. Only 23% of organisations have customer feedback loops that inform strategic decisions in functions like Product Design and Operations, while 28% have invested in real-time sustainability tracking. To bridge the gap between ambition and reality and set the stage for Industry 5.0, organisations must adopt a holistic, strategic approach. This includes establishing a value-driven tech strategy, leveraging core tech for cross-functional impact, treating #data as a strategic asset, preparing for rapid technology integration, and embedding Industry 5.0 thinking today. ai-driven-industry-5-0-apacs-maturity-gap #worlddatasummit #businessanalytics #machinelearning #dataanalytics

A lot of us want to enjoy our favorite movies without worrying about what it’s costing behind the scenes. That’s why knowing exactly how much #data Netflix uses and how to control it is very necessary. Netflix doesn’t charge by data, but your internet provider might. That’s why it’s useful to know how much you’re using each time you hit “Play.” Here’s a rough estimate of how much data Netflix uses per hour, depending on video quality: 🔝 Low quality (240p–480p): about 300MB per hour, 🔝 Standard Definition (SD): around 700MB per hour, 🔝 High Definition (HD): about 3GB per hour, 🔝 Ultra HD/4K: up to 7GB per hour. The difference can be massive. If you stream a two-hour movie in 4K, that’s roughly 14GB gone. Compare that to the same movie in low quality, which would use less than 1GB. Your data usage isn’t just about the video quality you pick. Several other factors can quietly increase how much data Netflix burns through: ▶️ Your default video quality settings: Netflix often picks the best quality based on your internet speed, not your data plan. If you don’t adjust it manually, you might be watching in HD or 4K without realizing it. ▶️ Device type: Streaming on a smart TV or laptop tends to use more data than on a phone. Bigger screens mean better resolution and that means more data. ▶️ Internet speed and stability: Fast, stable connections usually trigger higher video quality. Slower or unstable connections may default to lower quality, which saves data (even if the video looks slightly blurry). ▶️ Profile settings: Each profile on a Netflix account can have its own playback setting. If you set yours to “High” once, it sticks, until you change it again. ▶️ Autoplay and previews:  Netflix automatically plays trailers or the next episode. These silent streams also use data, even if you’re not actively watching. ▶️ Video length: The longer the movie or episode, the more data you use. A 20-minute sitcom at 3GB/hour (HD) might cost around 1GB. But a 2-hour movie in that same setting? That’s about 6GB gone. https://lnkd.in/dA7UQFCk #worlddatasummit #datacollection #dataquality #dataanalytics #bigdata

As #AI adoption accelerates and #cyberthreats increase, nearly 8 in 10 #IT security leaders in #APAC recognise their security practices need transformation. Across Asia Pacific, half (50%) worry their #data foundation isn’t set up to get the most out of agentic AI, and 57% aren’t fully confident they have the appropriate guardrails to deploy AI agents. In addition to a familiar slate of risks like #cloudsecurity threats, malware, and phishing attacks, IT leaders now cite data poisoning - in which malicious actors compromise AI training data sets - among their top concerns. Resources are rising in response: 76% of organisations expect to increase security budgets over the coming year. While 82% of IT security leaders believe #AIagents offer #compliance opportunities, such as improving adherence to global privacy laws, they acknowledge that AI agents also present compliance challenges. This stems partly from an increasingly complex and evolving regulatory environment across geographies and industries, compounded by compliance processes that remain largely unautomated and prone to error. ⚪ Just 52% are fully confident they can deploy AI agents in compliance with regulations and standards. ⚪ 85% of organisations say they haven’t fully automated their compliance processes. A recent consumer study found that trust in companies is on a precipitous decline, and six out of 10 (61%) consumers in APAC agree that advances in AI make a business’s trustworthiness more critical. Furthermore, 64% of consumers trust companies less than they did in 2023. IT security leaders see work to be done in earning this critical trust. ⚪ 51% aren’t fully confident in the accuracy or explainability of their AI outputs. ⚪ 54% don’t provide full transparency into how customer data is used in AI. ⚪ 54% haven’t perfected their ethical guidelines for AI use. apac-security-leaders-optimistic-about-agentic-ai-despite-readiness-gaps #worlddatasummit #datasecurity #dataquality #dataanalytics #bigdata

#AI, particularly #LLMs, is completely transforming the way people interact with data. Data users at all levels of experience and expertise, from first-timers to power users - are now able to pose complex questions in natural language to chatbots, to which they expect to promptly find, interpret, and present #datadriven insights packaged as pithy, accurate responses. For this evolution to be successful, AI systems need to get it right. This means the #data being accessed and interpreted by AI systems must first be evaluated, validated, structured, governed, and shared in ways that support the responsible and effective use of AI. In short, the data must be “AI-ready.” AI-ready development data is systematically organized and thoroughly documented to ensure its meaning and context are clear not only for subject matter experts, but also for general users and AI systems. Three core pillars define AI-ready development data: ➡️ AI-Ready Data Systems:  The foundational infrastructure - encompassing discovery platforms, APIs, and technical standards - ensures that data is not only stored but also readily discoverable, interoperable, and accessible. ➡️ High-Quality Data and #Metadata:  Reliable, up-to-date, and thoroughly documented data, accompanied by comprehensive and structured metadata. For AI applications, this entails datasets that are systematically organized and described with sufficient specificity to ensure both machine and human analysts can accurately interpret the information. ➡️ Robust Governance and Strategic Partnerships:  The implementation of comprehensive policies, standardized procedures, and collaborative efforts across sectors is essential to ensuring data integrity, enhancing transparency, and advancing responsible utilization. https://lnkd.in/d4qzmpGA #worlddatasummit #dataengineering #machinelearning #dataanalytics