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.
There is a moment that repeats itself across countless science-fiction stories. A ship’s sensors detect something unusual. Signals arrive that do not quite align with expectations. Perhaps it is a gravitational anomaly, a sudden communications blackout, or an unexpected hostile vessel appearing where none should exist. The bridge crew does not simply stare at the blinking lights. They interpret them. The captain asks the science officer what the signals mean, the engineer considers how the ship might respond, and the tactical officer evaluates defensive posture. Information becomes interpretation, interpretation becomes decision, and decision becomes action . . . capability.
In one of the latest articles on my website, I argued that GRC platforms must re-architect around digital twins, knowledge models, and agentic intelligence if they intend to survive the coming decade. But there is a deeper implication that deserves equal attention.
In my earlier piece, Risk Management Is Not a SOX Coloring Book: A Call for Risk Management as a Strategic Discipline, I argued that decades of Sarbanes-Oxley gravity have quietly reshaped how organizations understand risk—narrowing it into a compliance exercise defined by documentation, evidence trails, and audit satisfaction. That article challenged the idea that shaded boxes and completed control matrices equate to managing uncertainty. This follow-up goes a step further. It explores what risk management looks like once we finally put the coloring book down.
A week after publishing my first reflections on the World Economic Forum’s Global Risks Report 2026, I find myself returning to the same unease that prompted that first piece—not because the report needs more explanation, but because the initial reaction to it already feels familiar.
In my earlier reflections on enterprise risk intelligence, I focused on a fundamental realization: the world organizations now operate in no longer matches the way risk has traditionally been framed, assessed, or governed. That observation has continued to stay with me, not as an abstract idea, but as something I see play out repeatedly in conversations with boards, executives, and risk leaders across industries.
In a recent GRC Report piece, Risk Is Our Business: Why the GRC Market of 2030 Will Look Nothing Like Today, I argued that the governance, risk, and compliance market is not heading into another cycle of incremental change, but a structural break. The core claim was that risk has outgrown the architectures, assumptions, and mental models most GRC platforms and programs still rely on, and AI bolted onto legacy thinking will not save them.