What Is an AI Incident Response Plan?
An AI incident response plan is a documented set of procedures for identifying, responding to, and recovering from AI-related incidents. It defines what constitutes an incident, who is responsible for response, and what actions to take when things go wrong.
AI incidents are different from traditional IT incidents. They can involve biased outputs, unexpected behaviors, privacy violations, and decisions that harm individuals or groups. Your response plan must address these unique challenges.
Why You Need an AI Incident Response Plan
AI Systems Fail Differently
AI failures are often subtle. A model can perform well on average while consistently failing for certain groups. It can drift over time without obvious errors. You need procedures designed for these failure modes.
Speed Matters
When an AI system causes harm, rapid response limits damage. Without a plan, teams waste critical time figuring out what to do.
Regulatory Requirements
The EU AI Act and other regulations require incident reporting and response capabilities. A plan demonstrates readiness.
Types of AI Incidents
Performance Incidents
- Significant drop in accuracy or reliability
- Model drift beyond acceptable thresholds
- System unavailability affecting critical operations
Bias Incidents
- Discriminatory outcomes identified
- Unfair treatment of protected groups
- Complaints about biased decisions
Privacy Incidents
- Unauthorized data exposure
- Training data leakage
- Violation of data use agreements
Safety Incidents
- Harmful outputs or recommendations
- Physical harm from AI-controlled systems
- Dangerous misinformation generated
Incident Response Phases
1. Detection
How you identify incidents:
- Automated monitoring alerts
- User reports and complaints
- Internal audits and reviews
- External notifications
2. Triage
Initial assessment and classification:
- Confirm the incident is real
- Classify severity (Critical, High, Medium, Low)
- Identify affected systems and stakeholders
- Escalate according to severity
3. Containment
Limit the damage:
- Disable or rollback the AI system if needed
- Implement interim controls
- Preserve evidence for investigation
4. Investigation
Understand what happened:
- Root cause analysis
- Impact assessment
- Timeline reconstruction
- Documentation of findings
5. Remediation
Fix the problem:
- Implement corrective actions
- Test fixes before redeployment
- Update controls to prevent recurrence
6. Recovery
Return to normal operations:
- Gradual restoration of services
- Enhanced monitoring
- Stakeholder communication
7. Review
Learn from the incident:
- Post-incident review meeting
- Update incident response procedures
- Share lessons learned
Next Steps
Use our free Governance Checklist to assess your incident response readiness. The Documentation System includes incident log templates and response procedure frameworks.