Across large enterprises, boards are approving AI governance frameworks. The policy approval meeting has become a standard board agenda item: AI use case register, model risk policy, ethics principles, human oversight requirements. The vote passes. The governance record is clean.
The Netherlands Authority for the Financial Markets has warned that artificial intelligence is being adopted rapidly across the Dutch asset management sector, but many firms are still falling short on governance, policy, and internal controls.
Meta has paused its work with data vendor Mercor after a security breach that may have exposed sensitive elements of how leading AI models are trained. The decision, first reported by WIRED, is open-ended. For now, the work simply stops.
The White House has released a set of legislative recommendations outlining how Congress should approach artificial intelligence policy, offering a framework that spans child protection, economic infrastructure, intellectual property, and federal-state coordination. The March 2026 proposals stop short of introducing a single, overarching regulatory regime, instead setting out a series of targeted measures intended to guide AI development and oversight across sectors.
AI isn’t waiting for governance to catch up and that gap is quickly turning into one of the most serious risk challenges organizations face today. As companies push ahead with more advanced, increasingly autonomous AI systems, many are doing so without the controls needed to manage them effectively. What was once a manageable oversight issue is becoming something more structural. Agentic AI is beginning to operate beyond traditional human decision loops, and the longer governance lags behind, the harder it becomes to rein it back in.
In my most recent article on my site, I raised a concern that should not be easy to dismiss. The term “agentic AI” is being used far too loosely across the GRC market, often applied to capabilities that, while useful, fall well short of anything resembling true autonomy or orchestration.
Artificial Intelligence has officially entered the chat—and the conference room, the Slack channel, and, yes, the committee meeting that could have been an email. What started as a shiny IT initiative has now turned into a full-blown organizational identity crisis. Suddenly, everyone is asking the same questions: Who owns AI? Who governs it? Who explains it when it breaks? And, most importantly, does it get a seat at the table—or just a really big monitor in the back? The truth is, AI isn’t just another tool. It’s an organizational shapeshifter. It changes how work happens, who makes decisions, and how people engage with each other. It doesn’t just automate tasks; it rearranges responsibility. And that means the org chart—that sacred map of power, politics, and parking privileges—is about to look very different.