Every enterprise deploying AI agents at scale should assume, eventually, one will do something unexpected — leak sensitive data, take an unauthorized action, or produce harmful output. Whether that becomes a minor incident or a major crisis depends almost entirely on preparation done beforehand.
Build an AI-Specific Incident Response Plan
Traditional security incident response plans weren’t designed for autonomous systems that can take real-world actions on their own. Extend your existing incident response process with AI-specific playbooks: how to immediately pause or revoke an agent’s permissions, who gets notified, and how to assess the scope of an agent’s actions during the incident window.
Design for Fast Containment, Not Just Detection
Detecting an agent behaving badly matters less if there’s no fast way to stop it. Every production agent should have a clear, tested kill switch and scoped permissions that limit the maximum damage a single incident can cause, rather than broad standing access “just in case.”
Run Tabletop Exercises Before You Need Them
Walking through a realistic AI incident scenario with the relevant teams — security, legal, communications, the business owner — surfaces gaps in the response plan while the stakes are still hypothetical. Treat this the same way you’d treat any other critical system’s disaster recovery testing.
The enterprises that handle an AI incident well aren’t the ones who never have one — they’re the ones who prepared for it as a “when,” not an “if.”