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AI Incident Readiness Scorecard

Eight questions expose whether your team can identify, contain, communicate, and recover from a bad AI outcome without improvising under pressure. Choose the answer closest to your current operating reality.

No email requiredNo answers transmittedNo sensitive data requestedAbout three minutes
Contained synthetic storm above a black-glass incident strategy table
1. During an AI incident, who has authority to pause the workflow and coordinate decisions?
2. Can an operator stop risky AI actions without taking the whole business offline?
3. Can you identify the exact model, prompt, tools, data boundary, and configuration behind a disputed output?
4. Which AI actions require a human decision before they affect customers, money, access, or records?
5. How would your team know the AI workflow is failing before a customer reports it?
6. When was the last realistic recovery or tabletop drill for this workflow?
7. What happens when a model provider, vector store, identity service, or other critical dependency fails?
8. Can the team produce one accurate incident timeline, decision log, and stakeholder update?