AI Governance, Risk & Compliance
Designing an AI incident response playbook
Monitoring is incomplete without a response path. Organizations should decide in advance what happens when an AI system behaves outside an intended boundary.
Define incident classes
Examples can include unauthorized tool use, sensitive-data exposure, harmful external communication, unexpected autonomous behavior, material performance drift, security compromise or repeated policy conflict.
Establish containment options
Containment may mean disabling a tool, reducing permissions, switching the workflow back to human approval, isolating a data source, pausing the agent or rolling back a deployment.
Assign decision rights
Someone needs clear authority to pause a system. Someone needs ownership of investigation. Legal, compliance, security, operations and business leadership may have different roles depending on the event.
Learn without normalizing failure
After containment, document what happened, why existing controls did not prevent or detect it earlier, what changed, and how recurrence will be monitored. Incident review should improve the operating system rather than become a blame exercise.
Keep exploring
Turn the idea into an operating move.
Continue with a practical resource, a structured system, or an advisory conversation when context matters.
