Category: AI

  • AI Runs on Meaning

    by

    in

    In the first article of this series, I argued that most organizations don’t have an AI problem. They have a data problem. But that’s only a small part of the story. Because even organizations with enormous amounts of data often discover that their AI initiatives struggle for a completely different reason: The organization doesn’t understand…

  • Your Company Isn’t Ready for AI (And It Has Nothing to do with AI)

    by

    in

    Every executive meeting seems to have the same question these days: “What is our AI strategy?” It’s a very reasonable question. Artificial Intelligence is advancing rapidly, vendors are embedding AI into nearly every product, and organizations are feeling pressure to demonstrate that they are keeping pace. But after working with data platforms for years, I’ve…

  • When Governance Becomes Continuous

    by

    in

    For years, access governance has operated on a simple assumption: Review access periodically and hope the environment hasn’t changed faster than your governance process. That model made sense when: That world is gone. Modern environments change constantly. New: …appear faster than traditional governance processes can evaluate them. Which means the future of governance probably isn’t…

  • Governance Without Slowing Everyone Down

    by

    in

    At this point in the series, we’ve talked a lot about visibility, exposure, and risk. And that’s necessary. But eventually, every governance conversation runs into the same wall: “This sounds great… but people still need to get their jobs done.” That tension is real. Because the fastest way to make governance unpopular is to make…

  • Using AI to Improve Access Governance Instead of Making It Worse

    by

    in

    So far in this series, AI has mostly been the thing exposing the problem. And fairly so. AI amplifies access models.It traverses systems quickly.It exposes weak governance faster than most organizations are prepared for. But here’s the part that gets overlooked: AI can also become one of the most effective tools for understanding access complexity.…

  • How to Clean Up Access Control Without Breaking Everything

    by

    in

    At some point, every organization reaches the same conclusion: “We need to clean this mess up.” Usually after: That realization matters. But it’s also where many teams make a critical mistake: They treat access cleanup like a technical problem. It isn’t. It’s an operational problem wrapped around a technical system. And if you approach it…

  • Most AI Initiatives Don’t Fail for the Reason You Think

    by

    in

    Over the past few weeks, I’ve been writing about a pattern I’ve seen across a lot of data platforms: AI initiatives start strong… and then stall. Not because of talent.Not because of tooling. Because of architecture. Across different organizations, the pattern is surprisingly consistent: In fact, they’re the default path for many teams. But when…

  • From Legacy to AI -Ready: A Practical Modernization Roadmap

    by

    in

    Part 5 in a series on evolving SQL Server environments into AI-ready architectures. Once organizations recognize the architectural gap between traditional platforms and AI workloads, and understand why lift-and-shift migrations fall short, the next question becomes practical: How do we move forward without disrupting the systems that already work? For most teams, the answer isn’t…

  • Where SQL Server Meets AI: The Case for Hybrid Architecture

    by

    in

    Part 4 in a series on evolving SQL Server environments into AI-ready architectures. Simply moving SQL Server to the cloud isn’t enough. Lift-and-shift migrations reproduce the same bottlenecks — often at higher cost. The friction between traditional platforms and AI workloads persists. The solution isn’t abandoning SQL Server. It’s placing workloads where they belong: a hybrid…

  • The Lift-and-Shift Migration Trap (and Its Hidden Costs)

    by

    in

    Part 3 in a series on evolving SQL Server environments into AI-ready architectures. Once organizations recognize the architecture gap we discussed in a previous post, the natural instinct is often straightforward: “Let’s move the warehouse to the cloud.” Databases migrate. Pipelines move. Infrastructure changes. The environment is now technically modernized – cloud-based, scalable in theory, and…