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A practical look at AI governance for threat assessment: compare outputs from multiple models, record the assumptions behind each call, name the human who makes the final decision, and schedule a dated follow-up review

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Threat assessment teams are starting to use AI models to help sort risk signals, and the governance gaps are real

Compare where multiple AI models disagree, record the assumptions behind each threat call, name the human who owns the final decision, and set a follow-up review date that fits your risk level

A practical look at governing AI in threat assessment work

**Main blurb (83 words):** Running more than one AI model on the same threat assessment shows you where they disagree, and that's often the most useful part

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AI governance for threat assessment means keeping a clear record of how decisions get made. When multiple models disagree on a risk signal, that disagreement gets logged, not smoothed over