One signal

AI boards should define who can stop a project, what evidence would trigger intervention and how to roll it back, argues Desert Voice Ventures CEO Ana Mims in a Forbes essay. She also recommends setting the approved scope, risk limits and renewal date for each significant use case.

Mims’s point is that approval should not be a one-way door: management should return to the board when an AI system’s intended use expands, its data or vendor changes materially, a key control fails, or promised results do not arrive. That is one contributor’s governance advice, not a universal rulebook, but it gives boards concrete questions beyond the usual “is it accurate?”

Discuss: Should boards set formal stop-and-renewal criteria for every major AI use case, or would that pull them too far into management?

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