# AI incident response plan · [Product] · v[n] · [Date] Extends the company security incident process. Link: [process] ## AI-specific triggers - Confident wrong output affecting many users or a high-impact decision - Unsafe or unintended agent action - Prompt injection or tool misuse that changed system behavior - Personal or confidential data exposed through outputs - Fairness or bias finding - Unannounced behavior change after a model or provider update ## Severity | Level | Definition for this product | Example | Response time | |---|---|---|---| | 1 | | | | | 2 | | | | | 3 | | | | ## Controls available | Use case | Kill switch or degrade option | Who can trigger | Time to effect | |---|---|---|---| | | | | | ## Roles - Incident lead: [name] - PM (customer impact, comms, eval follow-up): [name] - Applied AI (diagnosis, model or prompt rollback): [name] - Security, privacy, legal: [names] ## Clocks to check (confirm with counsel) - Contractual notification commitments: [summary] - GDPR personal data breach notification, if personal data is involved - EU AI Act Article 73 serious incident reporting, for high-risk systems once applicable - Other: [jurisdiction or customer specific] ## Customer communication - First notice within [time], containing: what happened, what we changed, what customers should do, when we will update next. ## After the incident - [ ] Root cause (data, retrieval, prompt, model, tool, UX, process) - [ ] New eval cases added and passing - [ ] System card and impact assessment updated - [ ] Decision log entry - [ ] Tabletop scheduled for the next quarter