Building AI governance programmes that survive regulatory examination — inventory, consequence-based classification, accountable ownership, and the evidence trail examiners actually ask for.
Why the governed inventory is usually the only inventory anyone built, and what a vendor-embedded and shadow sweep surfaces that a policy review never will.
The difference between a committee and a name, and why unregistered automations fail the ownership test before they fail any technical one.
Autonomy times blast radius. Why classification by model sophistication produces the wrong control set, and how agentic systems tier differently.
The artifact pack an examiner can be walked through, and why lineage and retention evidence is the gate everything else depends on.
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