AI changed how you respond to incidents. Your tabletops haven't caught up.

As AI becomes embedded in incident response functions such as alert triage, playbook retrieval, response recommendations, and post-incident analysis, tabletop exercises must evaluate both human responders and the AI systems they depend on. AI-related failures may be subtle, including confident but incorrect summaries, outdated document retrieval, unsafe suggestions, outages, compromised tools, unclear human approval boundaries, and responders’ loss of manual investigation skills. Effective exercises should introduce failures in the AI layer, involve the teams that build and maintain the tools, test whether guardrails hold under pressure, and assess whether responders calibrate their trust appropriately rather than blindly following or ignoring AI output. Because models, retrieval sources, and controls change over time, organizations should regularly retest AI-assisted response processes, particularly as these tools become more central to security, SRE, support, and IT operations.

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