AI regulation is moving from awareness to execution. The challenge is turning requirements into controls, owners, evidence, and routines that can support audit, risk review, and management scrutiny. Three pressure points stand out. - Use case classification needs to be reliable: organisations must know where AI is used and what risk level applies. - Ownership needs to be assigned across IT, data, legal, security, procurement, and business teams. - Evidence needs to be maintained: decisions, controls, documentation, reviews, and vendor dependencies must be traceable. The working question is simple: how do we make AI compliance operational, useful, and sustainable over time? If you are preparing for these requirements, let’s compare how others are structuring the work.
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