This guide walks you through planning and running a tabletop exercise (TTX) for incident response in AI-assisted workflows. You’ll learn how to simulate a realistic AI-related incident, test your team’s decision-making, and uncover gaps in your response plans—all without triggering a real outage.
What You’ll Need
- A facilitator (someone who knows the workflow but isn’t a primary responder)
- A scribe to capture notes and action items
- Participants: security, IT, legal, communications, and business owners
- A scenario script (drafted in advance)
- Whiteboard or virtual collaboration tool (e.g., Miro, Mural)
- Current incident response plan and AI system documentation
- 1–2 hours of uninterrupted time
Step-by-Step
- Define objectives. Decide what you want to test: detection, containment, communication, or recovery. For AI workflows, common objectives include verifying data provenance, model behavior, and regulatory notification.
- Choose a scenario. Pick one that is realistic for your environment. Examples: a prompt injection that exfiltrates data, a model drift causing harmful outputs, or an unauthorized AI tool accessing sensitive data. Write a brief narrative with a trigger event.
- Identify participants. Invite the people who would actually respond. Include at least one person who understands the AI model’s lifecycle and one who owns the business process.
- Prepare injects. These are new pieces of information revealed during the exercise (e.g., a log showing unusual API calls, a customer complaint). Plan 3–5 injects to escalate the scenario.
- Set ground rules. Emphasize that the exercise is a no-blame learning event. No one is being evaluated; the goal is to find weaknesses in the plan.
- Run the exercise. The facilitator presents the initial scenario. Participants discuss what they would do, in what order, and who would be involved. The facilitator reveals injects at planned intervals.
- Document decisions. The scribe records key decisions, assumptions, and questions. Use a template with columns: time, action, owner, notes.
- Debrief. After the scenario, lead a structured discussion: What went well? What was unclear? What would you do differently? Capture action items with owners and deadlines.
- Write a report. Summarize findings, gaps, and recommendations. Share with participants and leadership. Schedule a follow-up to track progress.
Common Mistakes
- Making it too technical. Focus on process and communication, not deep technical details. Save those for a separate technical exercise.
- Not including business stakeholders. AI incidents often have regulatory or reputational implications. Legal and PR must be at the table.
- Letting the facilitator dominate. The facilitator should guide, not solve. Let participants struggle with decisions.
- Skipping the debrief. The exercise’s value is in the discussion after, not the scenario itself.
- Ignoring the “what if” of AI-specific issues. For example, how do you roll back a model? Can you trace a specific output to a training data point?
Tips
- Start with a low-stakes scenario if your team is new to TTX.
- Use a timer to keep the exercise moving. Allocate 10–15 minutes per inject.
- Encourage participants to think out loud. The value is in the reasoning.
- Have a “parking lot” for off-topic but important issues.
- After the exercise, update your incident response plan with lessons learned.
Troubleshooting
If the discussion stalls: The facilitator can ask probing questions like “What would you do first?” or “Who needs to be informed?”
If participants get stuck on details: Remind them that the exercise is about process, not exact commands. Say “Assume the technical fix is possible—what’s the decision path?”
If the scenario feels unrealistic: Pivot to a more plausible variant. You can adjust injects on the fly.
If the exercise runs too long: Skip or combine later injects. Prioritize the debrief.
If participants are silent: Use round-robin to get each person’s perspective. Ask each participant to state one action they would take.
Frequently Asked Questions
How often should we run a tabletop exercise for AI workflows? At least annually, or whenever you deploy a new AI system or change a significant workflow.
How long should the exercise be? Typically 1–2 hours. For complex scenarios, you can split into two sessions.
Who should be the facilitator? Someone who understands the workflow but isn’t a primary responder. An external facilitator can bring objectivity.
What if we don’t have an incident response plan yet? The exercise can still be valuable—it will highlight the need for one. Use the findings to build a plan.
Can we use a real incident as a scenario? Yes, but change details to avoid re-traumatizing the team and to prevent leaking sensitive info.
How do we measure success? Success is not “no mistakes” but that participants gain clarity on roles, decision paths, and gaps. A good exercise produces actionable improvements.
Related
Method: the standard formula for this calculation, rounded as each result states. See how the calculators work or report an error.
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