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𝗘𝘃𝗲𝗿𝘆 𝗔𝗜 𝘁𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻 𝗰𝗼𝗻𝘃𝗲𝗿𝘀𝗮𝘁𝗶𝗼𝗻 eventually hits the same wall. Not the strategy wall. The 𝗶𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 𝘄𝗮𝗹𝗹. 🎥 𝘚𝘦𝘦𝘯 𝘢 𝘳𝘦𝘦𝘭 𝘳𝘦𝘤𝘦𝘯𝘵𝘭𝘺 𝘵𝘩𝘢𝘵 𝗯𝗿𝗲𝗮𝗸𝘀 𝘁𝗵𝗶𝘀 𝗱𝗼𝘄𝗻 𝘀𝗶𝗺𝗽𝗹𝘆 𝘢𝘯𝘥 𝘵𝘩𝘢𝘵’𝘴 𝘦𝘹𝘢𝘤𝘵𝘭𝘺 𝘸𝘩𝘺 𝘪𝘵 𝗿𝗲𝘀𝗼𝗻𝗮𝘁𝗲𝘀. Thank you Shirin Khosravi Jam Five things between an organisation and a 𝗪𝗢𝗥𝗞𝗜𝗡𝗚 𝗔𝗜 𝘀𝘆𝘀𝘁𝗲𝗺: - A 𝗱𝗮𝘁𝗮 𝗽𝗶𝗽𝗲𝗹𝗶𝗻𝗲 - A 𝘃𝗲𝗰𝘁𝗼𝗿 𝘀𝘁𝗼𝗿𝗲 - An 𝗟𝗟𝗠 - An 𝗔𝗣𝗜 𝗹𝗮𝘆𝗲𝗿 - A 𝗰𝗼𝗻𝘁𝗮𝗶𝗻𝗲𝗿𝗶𝘀𝗮𝘁𝗶𝗼𝗻 𝗮𝗽𝗽𝗿𝗼𝗮𝗰𝗵 𝗧𝗵𝗮𝘁 𝗶𝘀 𝘁𝗵𝗲 𝘀𝘁𝗮𝗰𝗸. Everything else is commentary. But here is what the list does not show 👇 Each of those five components carries decisions that go well beyond the technical team. 🔹 The 𝗱𝗮𝘁𝗮 𝗽𝗶𝗽𝗲𝗹𝗶𝗻𝗲 raises 𝗱𝗮𝘁𝗮 𝗾𝘂𝗮𝗹𝗶𝘁𝘆 & 𝗹𝗶𝗻𝗲𝗮𝗴𝗲 questions → a 𝗴𝗼𝘃𝗲𝗿𝗻𝗮𝗻𝗰𝗲 conversation 🔹 The 𝘃𝗲𝗰𝘁𝗼𝗿 𝘀𝘁𝗼𝗿𝗲 raises questions about 𝗼𝗿𝗴𝗮𝗻𝗶𝘀𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗸𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 → who decided access? 🔹 The 𝗟𝗟𝗠 choice carries 𝗽𝗿𝗶𝘃𝗮𝗰𝘆, 𝗰𝗼𝘀𝘁 & 𝘀𝗼𝘃𝗲𝗿𝗲𝗶𝗴𝗻𝘁𝘆 implications → 𝗲𝘅𝗲𝗰𝘂𝘁𝗶𝘃𝗲 𝗼𝘄𝗻𝗲𝗿𝘀𝗵𝗶𝗽 🔹 The 𝗔𝗣𝗜 𝗹𝗮𝘆𝗲𝗿 is where 𝘀𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗽𝗼𝗹𝗶𝗰𝘆 meets 𝗔𝗜 𝗰𝗮𝗽𝗮𝗯𝗶𝗹𝗶𝘁𝘆 🔹 The 𝗰𝗼𝗻𝘁𝗮𝗶𝗻𝗲𝗿𝗶𝘀𝗮𝘁𝗶𝗼𝗻 approach determines whether this is 𝘀𝗰𝗮𝗹𝗮𝗯𝗹𝗲 & 𝗿𝗲𝗽𝗲𝗮𝘁𝗮𝗯𝗹𝗲… or just a one-time experiment 🚀 The organisations moving fastest on AI are not the ones with the biggest budgets. They are the ones where: 𝗔𝗥𝗖𝗛𝗜𝗧𝗘𝗖𝗧𝗨𝗥𝗘 𝗖𝗢𝗡𝗩𝗘𝗥𝗦𝗔𝗧𝗜𝗢𝗡𝗦 and 𝗕𝗨𝗦𝗜𝗡𝗘𝗦𝗦 𝗦𝗧𝗥𝗔𝗧𝗘𝗚𝗬 𝗖𝗢𝗡𝗩𝗘𝗥𝗦𝗔𝗧𝗜𝗢𝗡𝗦 …are happening 𝗶𝗻 𝘁𝗵𝗲 𝘀𝗮𝗺𝗲 𝗿𝗼𝗼𝗺, 𝗮𝘁 𝘁𝗵𝗲 𝘀𝗮𝗺𝗲 𝘁𝗶𝗺𝗲. ❓➡️ 𝘏𝘰𝘸 𝘸𝘦𝘭𝘭 𝗰𝗼𝗻𝗻𝗲𝗰𝘁𝗲𝗱 are those two conversations in your organisation? #AITransformation #EnterpriseArchitecture #AIStrategy #DataGovernance #DigitalTransformation #AIInfrastructure #ProductOwnership

AI and analytics are only as strong as the data platform behind them. But many Heads of Data are battling: • Fragmented sources • Over-engineered infrastructure • High operational overhead • Slow time to insight A modern data platform shouldn’t add complexity. It should remove it. DPaaS® simplifies how enterprises build, scale, and manage data platforms, accelerating insight, improving governance, and enabling AI at scale. See how DPaaS® supports enterprise data transformation at architechs.com.au. #DataStrategy #HeadOfData #DataPlatform #AITransformation

"I don't know what I don't know." For most CIOs and IT Directors, this is the silent risk lurking within their data architecture. As leadership teams push for rapid AI adoption, the foundational challenge isn't the AI itself—it's the Indexation. In this week’s episode of The Digital Exchange, I’m joined by Jaap Mantel to discuss why data classification is no longer just a "checking the box" exercise for compliance. It is the bedrock of operational resilience. Jaap shares a sobering reality: if a major platform like Workday is compromised, 100% of your unfiltered data could be exposed on the dark web if you haven't accurately identified and mapped your environment. For organizations managing thousands of employees, this visibility is also the key to Microsoft license optimization. You cannot strategically deploy high-level security or AI features like Copilot if you are operating with a blind spot. Modern governance isn't about limiting access; it's about having a 100% overview of what exists, where it lives, and who owns it. Are you making decisions based on data, or based on assumptions? Catch the full conversation with Jaap in the comments below. 👇 #ExecutiveLeadership #AIGovernance #DataStrategy #Microsoft365 #DigitalTransformation #TheDigitalExchange #DataClassification

𝗔𝗜 𝗶𝘀 𝗺𝗼𝘃𝗶𝗻𝗴 𝗳𝗮𝘀𝘁. 𝗠𝗼𝘀𝘁 𝗲𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲𝘀 𝗮𝗿𝗲 𝗻𝗼𝘁 𝗿𝗲𝗮𝗱𝘆 𝗳𝗼𝗿 𝘄𝗵𝗮𝘁 𝗰𝗼𝗺𝗲𝘀 𝗻𝗲𝘅𝘁. 𝗢𝗻𝗹𝘆 𝟭𝟭% 𝗵𝗮𝘃𝗲 𝗮 𝗰𝗹𝗲𝗮𝗿 𝗿𝗼𝗮𝗱𝗺𝗮𝗽 𝘁𝗼 𝗱𝗲𝗽𝗹𝗼𝘆 𝗔𝗜 𝗮𝘁 𝗲𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲 𝘀𝗰𝗮𝗹𝗲. The problem isn't the technology. It's the architecture: ❌ Your AI tools are creating ungoverned access points ❌ Your sensitive data ends up on infrastructure you don't control ❌ Your scaling stalls when costs become impossible to forecast If any of this sounds familiar, this is for you. We put together a free whitepaper to help you move from AI experimentation to enterprise-wide deployment without losing control of your data, governance, or budget. Download here 👉 https://lnkd.in/daX9fdns #AI #Enterprise #Governance #DataSovereignty #SeldonIA (source: KPMG, 2026)

#DataManagement Most enterprises don’t have a data shortage - they have a latency crisis. The era of the "batch pipeline" is over. In a high-velocity landscape, data that moves in intervals is already obsolete by the time it reaches a dashboard. This isn't just a technical delay; it is an intelligence gap that stalls decision-making and weakens AI initiatives. Cloudangles helps enterprises move beyond fragmented pipelines to continuous data systems. We architect unified ecosystems where data doesn’t just move - it flows, governs, and optimizes itself in real time. By integrating agentic intelligence into your data operations, we ensure your infrastructure is always reliable, always scalable, and fundamentally AI-ready. Stop managing pipelines. Start running data as a system. Read more: https://lnkd.in/guYFY3jN #DataEngineering #RealTimeData #AgenticAI #Cloudangles #EnterpriseIntelligence

Why Data Governance Is Broken Let’s be honest about the current state of data governance. In many organizations, it looks like this: • Different teams managing different datasets • Multiple tools that don’t talk to each other • Policies defined in silos • Governance applied inconsistently The result? ❌ Policy conflicts ❌ Duplicate work ❌ Gaps in data protection ❌ Reactive firefighting instead of proactive control This fragmented approach simply doesn’t scale—especially in a world of: • Multi-cloud • SaaS applications • Real-time data • AI-driven use cases Data governance today is often bottom-up and tool-driven. What we actually need is top-down, unified, and automated governance. Until that shift happens, organizations will continue to struggle—no matter how many tools they buy. #DataGovernance #Data #AI #DataStrategy #DigitalTransformation

Many enterprises already have vast amounts of data. Yet business teams still struggle to rely on it when making critical decisions. The issue often lies in ownership and trust. When data sits in silos or lacks clear accountability, teams fall back on manual work and disconnected reports. As AI and real-time decision systems become central to business operations, organizations need data that is reliable, governed, and easy to reuse across functions. That’s why forward-thinking enterprises are beginning to treat datasets like products with defined owners, standards, and interoperability across teams. Discover how Wissen supports enterprises in building governed, analytics-ready data platforms designed for scale: https://www.wissen.com/ #WissenTechnology #DataStrategy #DataEngineering #DataManagement #DataGovernance

Still not seeing ROI from your data modernization efforts? You’re not alone. Many organizations invest heavily in platforms—but overlook the fundamentals: • Data quality • Ownership • Engineering practices The result? More complexity, less value. This whitepaper breaks down how leading organizations are shifting to a product-oriented data strategy unlocking faster insights, better governance and AI that actually works. 📥 Get the insights: https://lnkd.in/eEUv8FH9

Modernization isn’t just about platforms and cloud. Thoughtworks’ new whitepaper shows why getting the data foundation right is the real game‑change Get the insights: https://lnkd.in/eEUv8FH9