The first-24-hours playbook for harmful outputs

An AI incident response plan

Purpose and scope

This playbook covers what to do in the first 24 hours after an AI system produces harmful, unsafe, discriminatory, or otherwise unacceptable outputs. “Harmful outputs” includes content that could injure a person, expose sensitive data, drive unfair outcomes, violate policy, or create legal or reputational risk. This plan assumes facts are incomplete at the start. It is designed to stabilize trust while you regain control of the system.

This is not a postmortem template. This is the “stop the bleeding, learn fast, communicate cleanly” plan. Adapt it to your industry obligations and consult counsel for regulatory, contractual, and notification requirements.

What “good” looks like in 24 hours

By the end of Day 1, you want five things to be true.

1. You have contained harm. You reduced or stopped the harmful outputs in production, or you isolated the affected pathway.

2. You have protected people. You have a path to handle impacted users, escalation for safety risks, and a clear support motion.

3. You have an honest narrative. You can explain what happened at a high level without guessing.

4. You have preserved evidence. You can reconstruct what the system did and why.

5. You have a decision owner. One accountable leader is coordinating actions, tradeoffs, and communications.

Roles. Who does what

Name these roles in advance. During the incident, do not improvise ownership.

• Incident Commander (IC). Runs the playbook, owns the timeline, assigns work, approves updates.

• AI Technical Lead. Leads diagnosis, mitigation, and system changes.

• Product Lead. Owns customer impact, feature flags, and product decisions.

• Trust and Safety Lead. Owns harm taxonomy, user safety actions, and content handling.

• Security Lead. Owns evidence integrity, access controls, and potential data exposure.

• Legal and Compliance Lead. Advises on liability, notifications, retention, and statements.

• Communications Lead. Owns internal and external messaging, cadence, and approvals.

• Customer Support Lead. Owns front-line scripts, surge handling, and case tracking.

• Executive Sponsor. Clears major decisions fast. Owns board-level reporting.

• Scribe. Documents every decision, time, and action. This is not optional.

If you cannot staff all roles, combine them. Never combine IC with the person doing deep technical debugging. The IC must stay above the weeds.

Severity levels. Decide fast

Use a simple severity scheme so the team moves in one direction.

SEV 1. Credible risk of physical harm, self-harm, illegal instructions, child safety issues, or broad exposure of sensitive data. Also includes widespread discriminatory outcomes, or major customer and partner disruption.
SEV 2. Harmful outputs with limited scope. Material reputational risk. Confirmed policy violations. No clear sensitive data exposure.
SEV 3. Isolated harmful outputs. Low scale. Contained. No meaningful downstream impact.
SEV 4. Near miss. Caught in testing or monitoring before user impact.

Default to a higher severity when facts are unclear. You can always downgrade later. You cannot undo the cost of moving too slowly.

The first hour. Triage and contain

0 to 15 minutes. Declare and stabilize

• Declare the incident. Name it. “Harmful outputs in production.” Assign SEV level.

• Appoint the IC and Scribe. Start the incident log immediately.

• Freeze risky changes. Pause non-essential releases to the affected system.

• Create a single source of truth. One incident doc. One timeline. One decision log.

• Start a tight update cadence. Every 30 minutes for SEV 1, every 60 minutes for SEV 2.

15 to 30 minutes. Stop new harm

Pick the fastest safe containment action. You are buying time.

Containment options, from fastest to more involved:

• Disable the feature or route. Turn it off if safety is at risk.

• Reduce exposure. Limit to internal users, a small cohort, or lower-risk geographies.

• Add human review. Require approval for outputs in the affected category.

• Add safe-mode constraints. Narrow what the system can do while you investigate.

• Block the prompt pattern. If a narrow trigger is known, block it.

• Rollback. Revert to the last known good configuration.

Decision rule: if you cannot explain why harm is happening, reduce the blast radius immediately. Speed beats elegance in the first hour.

30 to 60 minutes. Preserve evidence

You need enough fidelity to learn what happened without contaminating it.

• Snapshot key logs. Inputs, outputs, system messages, routing decisions, and user context.

• Record configuration state. Versions, policies, runtime settings, and any recent changes.

• Capture examples. Save representative harmful outputs with timestamps and IDs.

• Restrict access. Limit who can view sensitive incident artifacts.

• Start a case list. Identify affected users, partners, and impacted workflows.

If there is any chance of sensitive data exposure, treat this like a security incident. Pull security into the core.

Hours 1 to 4. Diagnose and control the pathway

Build a shared understanding

Your first objective is not “root cause.” It is “mechanism.” What path produced the harm.

Answer these in plain language:

• What did the user experience.

• Who was affected, and how many.

• When did it start.

• What changed recently.

• What system pathway produced the output.

• What safeguards failed or were bypassed.

Common causes of harmful outputs

You will often find one of these patterns.

• Prompt or policy drift. Instructions changed, and safety constraints weakened.

• Data leakage. The system is echoing sensitive information from context.

• Tool or action misuse. The system is taking actions it should not.

• Routing errors. Unsafe pathway used for a high-risk request.

• Guardrail gaps. Missing rules for a scenario the real world just created.

• Evaluation blind spots. Your tests did not reflect real user behavior.

• Unbounded autonomy. The system acted with too much freedom under pressure.

• Feedback loop. User interactions amplified the worst behavior.

Do not debate the “philosophy” of AI safety in the first four hours. Focus on the mechanism and containment.

Decision checkpoints

At hours 2 and 4, the IC runs a decision checkpoint with the executive sponsor.

• Is harm fully stopped. If not, why.

• Is sensitive data involved. If unsure, treat as “possibly yes.”

• Are customers materially impacted. If yes, what is the support motion.

• Do we need an external statement today.

• What is the next safe operating mode.

Communications. Start early, stay honest

Silence creates rumors. Overconfidence creates liability. Your job is steady, factual communication.

Internal message within 2 hours

Send a short internal note to leadership and frontline teams.

Include:

• What happened, in one sentence.

• What you have done to contain it.

• What people should and should not say externally.

• Where updates will be posted, and when the next update arrives.

• How to escalate new reports.

Customer support script within 2 hours

Support needs a script that is calm and consistent.

Include:

• Acknowledgment.

• Immediate safety guidance if relevant.

• What you are doing now.

• How you will follow up.

• How to report examples.

Avoid: blaming users, minimizing, or speculating.

External statement. Only if needed

If SEV 1 or high-visibility SEV 2, prepare a holding statement. Use it if the issue is visible or likely to become public.

A good holding statement:

• Confirms you are aware.

• States you have taken steps to limit impact.

• Commits to updates.

• Provides a support channel.

• Avoids technical details and avoids guessing.

Hours 4 to 8. Move from containment to corrective action

Define “safe to reopen” criteria

Before you turn anything back on, define the criteria.

Examples:

• Harmful output rate below a clear threshold.

• High-risk categories blocked or human-reviewed.

• Monitoring alerts in place and tested.

• A rollback plan ready if harm returns.

• Support and comms ready if users report issues.

Patch strategy

Pick the smallest change that restores safety and stability.

• Tighten constraints and refuse risky categories.

• Improve filtering and detection around known triggers.

• Add step-up verification for sensitive contexts.

• Increase friction for edge cases that create harm.

• Expand coverage of forbidden or restricted content.

• Strengthen routing so high-risk requests go to safer handling.

Remember. A perfect fix that takes two days is not a Day 1 fix.

Validate with rapid tests

Use real incident examples plus a broader test set.

• Reproduce the harm. Confirm you can trigger it.

• Apply mitigation. Confirm you cannot trigger it.

• Check for regressions. Confirm normal behavior still works.

• Run “abuse” tests. Confirm known misuse patterns fail safely.

• Document results in the incident log.

Hours 8 to 12. Prepare disclosures and obligations

This is where Legal and Compliance earn their keep. You want controlled, early decisions on obligations.

Obligation review checklist

• Contractual reporting duties to partners.

• Industry and geographic notification rules.

• Consumer protection and advertising implications.

• Data protection obligations if personal data may be involved.

• Record retention and litigation hold requirements.

Even if you do not notify today, you want the decision documented today.

Stakeholder mapping

List the stakeholders and rank them by urgency and impact.

• Impacted users.

• Key customers and partners.

• Regulators or oversight bodies.

• Internal leadership and board.

• Employees, especially customer-facing teams.

• Media, if the issue is public.

Hours 12 to 24. Reopen carefully and stabilize trust

Controlled rollout

If you are reopening, do it in a staged way.

• Start small. Internal users or a low-risk segment.

• Watch metrics closely.

• Keep human review for high-risk categories.

• Maintain the faster update cadence until stable.

• Be ready to shut it back down quickly.

Day 1 board and exec update

Provide a one-page update that is factual and action-oriented.

Include:

• Summary of incident and impact.

• Containment actions taken and current operating mode.

• Preliminary mechanism and what is still unknown.

• User safety actions and customer support posture.

• Communications sent and planned.

• Next 48-hour plan with owners.

• Risks. What could still go wrong.

Close the first-day loop with frontline teams

Support teams and customer-facing staff should hear from leadership again within 24 hours. They are your trust channel.

Monitoring and metrics that matter

During and after the first day, track a small set of signal metrics.

• Rate of harmful outputs per 1,000 interactions.

• High-risk category trigger counts.

• User reports per hour, and resolution time.

• Impacted user count and severity distribution.

• Escalations to safety or legal.

• Rollback or fail-safe activations.

• Customer sentiment indicators where available.

Do not drown the team in dashboards. Pick signals that drive action.

Templates you can copy and use

Incident brief. First update (internal)

Subject: AI incident. Harmful outputs. Containment in progress
What happened: We identified harmful outputs from an AI feature in production.
What we did: We [disabled or limited] the feature to reduce exposure while we investigate.
What we know: Impact appears to be [scope]. We are still confirming facts.
What to do: If you see examples, report them to [channel]. Do not share details externally.
Next update: [time], then every [cadence].
Owner: [Incident Commander name].

Customer support script. First response

Thank you for flagging this. We are aware of an issue where our AI feature produced an inappropriate response. We have taken immediate steps to reduce impact while we investigate. If you can share the time and a screenshot or copy of the output, it will help us resolve this faster. If you feel unsafe or at risk due to the content, please stop using the feature and contact [support channel] for priority help.

External holding statement. If needed

We are investigating reports that an AI feature produced inappropriate outputs. We have taken steps to limit impact while we work to understand the cause. We will provide updates as we learn more. If you encountered this issue, please contact [support channel] and share details so we can assist.

After 24 hours. The handoff to the deeper work

Day 2 is where you run a proper root cause analysis, expand evaluation coverage, harden governance, and publish a transparent post-incident report where appropriate. The first day is about control, safety, and credibility. If you achieve those three, you have earned the right to take the time to fix the system well.

If you want, tell me what kind of harmful outputs you mean most in your world. Safety risk, discrimination, sensitive data leakage, or brand and policy violations. I can tailor this playbook into a tighter version with your severity triggers, your stakeholder map, and ready-to-use comms for that scenario.