Recall the core questions for an AI risk review.
GOVERN question Who owns policy, approval, escalation, and residual risk for this AI use case? No owner means risk will be discovered by whoever is unlucky later. MAP question Who could be harmed, in which workflow, if the AI output is wrong or over-trusted? Context turns generic AI risk into leadership risk. The vendor says the model is accurate enough. Your line Good. What did we measure in our context, with our users, and what is the escalation path when it fails? Accepting vendor accuracy as operating evidence. It separates model claims from use-case trustworthiness. Pilot approval vs scale approval…
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