An AI incident response plan should tell your organization how to detect and assess an event, limit harm, preserve evidence, investigate causes, meet any applicable reporting duties, communicate with affected people, and restore service safely. Build it around the systems you actually operate: name decision-makers and backups, document dependencies and known limits, and specify who can pause, constrain, roll back, or deactivate each system.
What an AI incident response plan needs to do
An AI incident is not necessarily just a model producing a bad answer. Harm can arise from the model, the data pipeline, prompts or instructions, connected tools, access controls, human workflows, a provider change, or the way an output affects a downstream decision. The plan should cover the whole deployed system and its effects—not only the model itself.
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Use the plan alongside your organization’s security, privacy, safety, and business-continuity procedures. Make clear which existing process takes precedence when an event crosses boundaries, and who coordinates the response when more than one team is involved.
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NIST’s AI Risk Management Framework (AI RMF) 1.0 is voluntary guidance for managing AI risks across design, development, use, and evaluation. NIST released it on January 26, 2023 and has said it is being revised. Its companion AI RMF Playbook suggests actions, but NIST says it is “neither a checklist nor set of steps to be followed in its entirety”; the Playbook page says it will be updated after the framework revision. Use both as aids to tailor your own process, not as a substitute for organization-specific decisions.
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1. Establish scope, ownership, and decision authority
Start by deciding which AI systems the plan covers: production models, AI-enabled features, internally built tools, third-party services, and systems used by staff to make or support consequential decisions. Set a process for bringing new systems and material changes into scope.
For each covered system, identify a response lead and a backup, then assign an accountable owner to each decision and action. A contact list alone is not enough: responders need to know who has authority to act, especially outside normal working hours.
- Incident lead: coordinates triage, assigns work, maintains the incident record, and escalates decisions.
- System owner and operators: explain the deployment and dependencies, carry out approved technical changes, and assess service restoration.
- Security and privacy contacts: assess compromise, exposure, and handling of sensitive records.
- Legal and compliance contacts: assess applicable duties, reporting routes, and deadlines.
- Domain and safety experts: assess the significance of outputs and possible effects on people.
- Communications and user-support contacts: prepare notices, respond to questions, and provide routes for appeal or recourse.
- Vendor or model-provider contacts: provide escalation paths for hosted models, infrastructure, data, and other third-party components.
For each action—such as switching to human review, disabling a feature, rolling back a release, or deactivating a service—record the authorized decision-maker, backup, implementation owner, and any required consultation. Define who may take an urgent protective action before the full response team is assembled, and how that action is reviewed and documented afterward.
2. Create a usable inventory before deployment
Responders cannot identify the scope of an incident if they do not know what is running, what changed, or where its outputs go. Maintain a current inventory for each system and make the relevant record accessible to the response team.
- Purpose and context: intended use, prohibited or out-of-scope uses, users, deployment sites, and the people or communities affected.
- System map: model and version, data sources and pipelines, prompts or instructions, connected tools, interfaces, integrations, and critical downstream decisions.
- Risk profile: known limitations, baseline performance, relevant safety measures, criticality, and the organization’s tolerance for residual risk.
- Change history: versions and dates for models, data, prompts, policies, tools, integrations, configuration, and provider changes.
- Response details: system owner, technical contacts, escalation route, approved containment options, validated fallback, and provider support contacts.
Record changes in a way responders can compare with the last known working state. This is particularly important when a third party supplies a pretrained model, hosting, data, or a connected service: an incident may involve a component your organization does not directly control. NIST’s AI RMF calls for documenting risks, tracking third-party risks, and monitoring pretrained models.
3. Define intake, triage, and escalation triggers
People affected by a system may notice a problem before a monitoring alert does. Provide more than one intake route, and make sure reports reach the response team rather than disappearing into general customer support or security queues.
- Monitoring alerts and operational dashboards
- Staff and contractor reports
- End-user complaints, appeals, and requests for correction
- Feedback from affected communities or domain experts
- Security reports, vendors, model providers, and infrastructure partners
Give staff a short reporting form or channel that captures what happened, when and where it happened, which system was involved, the suspected impact, and how to contact the reporter. Do not require a reporter to decide whether an event is legally reportable before escalating it.
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| Planning level | Example trigger | Response expectation to define |
|---|---|---|
| Critical | Credible risk of severe or widespread harm; a serious compromise; or an unsafe autonomous action affecting people or critical operations. | Immediate escalation to the incident lead and authorized decision-maker; assess urgent containment and any time-sensitive reporting duty. |
| High | Material harm, sensitive data exposure, harmful disparate outcomes, or an outage affecting an important service, with scope or cause still uncertain. | Prompt specialist review, impact scoping, evidence preservation, and a documented containment decision. |
| Moderate | A bounded failure or drift with limited observed effects, but a plausible path to further harm or recurrence. | Assign an owner and review time; assess whether limits, added monitoring, or a controlled change are needed. |
| Low or monitored issue | An anomaly or complaint with no established material impact and no current indication of escalation. | Record and monitor it, set criteria for raising severity, and retain a route for new evidence or appeals. |
Potential AI-specific triggers include unsafe or materially incorrect outputs; performance drift; harmful disparate outcomes; privacy loss or data leakage; model or infrastructure compromise; prompt injection or misuse; unauthorized changes; unavailable or degraded service; unexpected autonomous action; and failures in model, data, or other third-party dependencies. These are prompts for incident-plan design, not a claim that every event is legally reportable.
4. Preserve evidence and protect sensitive records
As soon as an incident is suspected, record what is known and preserve relevant evidence without collecting more personal or sensitive information than is necessary. The incident lead should assign an evidence owner and ensure records are protected from alteration or inappropriate access.
Depending on the event and applicable privacy rules, evidence may include:
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- Times, time zones, detection source, and actions taken
- System, model, data, prompt, policy, tool, and integration versions
- Relevant prompts or inputs, outputs, tool calls, and affected decisions
- Logs, alerts, configuration changes, access records, and provider notices
- Known limitations, baseline measures, and the evidence supporting the initial severity assessment
- Who collected or handled each record and when
Preserve prompts, inputs, and outputs only where lawful and necessary; they may contain personal, confidential, or otherwise sensitive information. Restrict access, follow retention rules, and document chain of custody where the evidence may be needed for a formal investigation. Coordinate containment with evidence preservation so a rollback, shutdown, or configuration change does not unnecessarily erase the information needed to understand the cause.
5. Choose containment that limits harm without making recovery harder
Containment is a decision, not a single default action. The safest choice depends on the potential harm, the reliability of the available evidence, the reversibility of the intervention, and the effect of interruption on people who depend on the service. Specify who authorizes each option and who implements it.
| Containment option | When it may fit | Trade-off to assess |
|---|---|---|
| Disable an affected feature or capability | The issue is localized and the remaining service can operate safely. | May reduce service impact while leaving other system paths active; verify the feature is actually disabled. |
| Rate-limit or isolate the service | Reducing volume or separating a component can reduce exposure while investigation continues. | May not stop a harmful behavior entirely and can affect legitimate users. |
| Route cases to human review | Outputs need contextual judgment or consequential decisions should pause pending review. | Human reviewers need capacity, suitable guidance, and authority to override or correct outputs. |
| Switch to a validated fallback | A tested alternative can maintain service with an acceptable risk profile. | Confirm the fallback is suitable for the same context and does not introduce a different failure mode. |
| Roll back a change | A recent model, data, prompt, policy, tool, or configuration change is plausibly related. | Preserve the changed-state evidence and verify that the earlier version is still safe and supported. |
| Deactivate the system | Continued operation presents unacceptable risk or narrower controls are ineffective. | Plan for dependent workflows, user communication, and a controlled route to restore service. |
For every option, state the trigger, approver, implementer, expected result, verification method, and conditions for escalation or reversal. If an immediate action is needed to prevent further harm, record why it was taken, what evidence was preserved, and who will review the decision.
6. Investigate impact and cause
Separate established facts from hypotheses. The investigation should determine what happened, who or what was affected, whether the problem is continuing, and what evidence would confirm or disprove the suspected cause. Track uncertainty explicitly instead of presenting an early explanation as a conclusion.
Assess direct and indirect effects on users, affected communities, safety, rights, privacy, security, and downstream systems. Look beyond model behavior: examine data pipelines, instructions and prompts, connected tools, access controls, human workflows, operational changes, and provider updates. A model output may be the visible symptom while the underlying failure lies elsewhere.
Coordinate with vendors or providers when a component they control may be involved. Record what was requested, what evidence or explanation was supplied, and any limits on your ability to verify their account. NIST’s AI RMF calls for tracking risks over time, using user feedback and appeals, assessing impacts, and managing third-party risks.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.7. Assess legal duties separately from internal severity
Do not treat an internal severity level as a legal classification. Reporting duties depend on jurisdiction, sector, system classification, the organization’s role, the event, and the applicable law. Assign legal or compliance staff to identify the relevant rules, authority, reporting route, trigger, deadline, and required content. Record the decision and its basis even when the conclusion is that no report is required.
For the EU AI Act, Article 73 concerns serious incidents involving covered high-risk AI systems; it does not make every AI tool or every operational incident reportable. Determine whether the system, the organization’s role, and the event meet the applicable definitions, and assess any equivalent reporting regime that affects the route.
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1Repair Windows errors before they cause bigger problems2Fix the driver behind crashes, sound loss and screen glitches3Clear out junk files and repair common Windows errorsFor covered Article 73 cases, the Commission-hosted regulation text sets a general deadline of immediately after establishing a causal link or a reasonable likelihood of a serious incident, and no later than 15 days after awareness. It specifies a no-later-than-two-day limit for specified widespread-infringement or serious-incident cases, and no later than 10 days for a death-related case. These are legal limits for covered cases, not recommended internal response targets. Article 73(5) allows an incomplete initial report followed by a complete report where necessary to ensure timely reporting. The same text requires the provider to investigate, assess risk, take corrective action, and cooperate with authorities; it also restricts certain alterations that could affect evaluation of the cause before authorities are informed. Check the current consolidated text and obtain appropriate legal advice for a specific event.
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There is a separate applicability question for providers of general-purpose AI models with systemic risk. The European Commission FAQ says such providers must track, document, and report serious incidents and corrective measures without undue delay to the AI Office and, as appropriate, national competent authorities. It describes serious cybersecurity breaches relating to a model or its physical infrastructure, including model-parameter exfiltration and cyberattacks, as potentially relevant where specified obligations may be implicated. Assess this separately from Article 73 rather than assuming that one regime covers the other.
8. Communicate with affected people and other stakeholders
Prepare communication paths for affected users, customers, employees, regulators, vendors, and other relevant AI actors. Decide who approves notices, who sends them, and how people can ask questions or seek review. Coordinate external communications with legal and privacy review without delaying urgent protective information when disclosure is required or needed to reduce harm.
A useful incident notice distinguishes confirmed facts from what remains uncertain. Explain the known effects, actions taken to limit harm, steps recipients can take, available recourse, and when they should expect another update. Avoid unsupported assurances about scope or cause; update the notice when material facts change.
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Do not equate a service coming back online with a resolved incident. Before restoration, the system owner and the appropriate risk authority should review corrective actions, relevant performance and safety measures, and the evidence that the original failure is controlled.
- Correct: address the confirmed cause or reduce the risk when the cause remains uncertain; document any temporary safeguards.
- Validate: test the affected behavior and relevant adjacent functions against measures appropriate to the system and incident.
- Approve: record who accepted the remaining risk and authorized restoration, including any conditions or restrictions.
- Restore in a controlled way: use staged or limited resumption where appropriate, with a clear rollback path.
- Monitor: increase monitoring for recurrence and define thresholds for renewed containment or escalation.
10. Close the loop with review, exercises, and maintenance
Keep the incident open until assigned corrective actions have owners and due dates, the recovery decision is recorded, and required communications and reports have been handled. A post-incident review should identify what worked, what failed, unresolved uncertainty, and changes needed to prevent recurrence.
Feed the findings into system tests, monitoring, documentation, staff training, third-party oversight, the risk register, and the response plan. Schedule exercises that reflect realistic AI failure modes, such as a harmful output, a privacy exposure, a provider-side change, or a tool acting unexpectedly. Verify that after-hours contacts, authority to contain, provider routes, evidence access, and communication approvals still work. Maintain document version control so responders can identify the current plan and the systems it covers.
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