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An effective AI incident response plan extends your organization’s existing cybersecurity process: it identifies which AI systems are in scope, assigns decision-makers, sets triage and evidence procedures, and explains how to contain and safely restore affected services. Use NIST SP 800-61 Rev. 3 as the organization-wide foundation, then add AI-specific procedures tailored to your systems and obligations.
Start with your existing incident-response framework
NIST finalized SP 800-61 Rev. 3 in April 2025, superseding Rev. 2. It integrates incident response with the wider cybersecurity risk-management lifecycle rather than treating response as a stand-alone emergency manual. NIST summarizes the principle this way: “Incident response is a critical part of cybersecurity risk management and should be integrated across organizational operations.”
Use its six functions to organize the plan. The AI-specific material in NIST IR 8596 can inform additions, but that publication is an initial preliminary draft dated December 2025—not a final standard. NIST AI RMF 1.0 is voluntary, and NIST says it is being revised. Neither source makes this plan a universal legal checklist.
| NIST function | What to establish for AI response |
|---|---|
| Govern | Set ownership, decision authority, escalation, and review of AI incident procedures. |
| Identify | Know which AI systems, providers, data, and business operations could be affected. |
| Protect | Maintain access controls, backups, fallback processes, and evidence-retention arrangements that support response. |
| Detect | Define how reports and signals involving AI services are recognized and routed. |
| Respond | Validate reports, assess impact, preserve evidence, contain the incident, and coordinate communications. |
| Recover | Approve restoration, validate the system before returning it to service, and apply lessons to improve the program. |
The functions are connected: lessons from incidents and exercises should feed changes to governance, safeguards, detection, and recovery procedures.
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1. Set scope, ownership, and decision authority
Write down what the plan covers before an incident forces the question. Include AI systems that can affect organizational data or operations, whether built internally, hosted by a supplier, or embedded in another product. Identify the business processes that depend on them, relevant environments, data dependencies, and providers.
Adapt the roles below to your organization. One person may hold more than one role, but the plan should still identify who performs each function and who has authority to act.
- Incident commander: coordinates the response and records decisions.
- Security lead: directs investigation, technical triage, and evidence handling.
- AI system or business owner: explains intended use, operational impact, and acceptable fallback options.
- IT or operations lead: carries out approved isolation, access changes, rollback, or restoration.
- Privacy and legal contacts: assess data, regulatory, contractual, and other legal implications.
- Communications lead: prepares approved internal and external messages.
- Provider contacts: coordinate with relevant AI, cloud, data, and other service suppliers.
Specify who may declare an incident, set its severity, approve service interruption, isolate or shut down a technology asset, and authorize recovery. Include an escalation route if the usual approver is unavailable. NIST’s general incident-response policy guidance calls for clear scope, roles, responsibilities, authorities, severity guidance, and recovery procedures.
2. Build an AI system inventory responders can use
A responder needs to identify the affected service and its dependencies quickly. Maintain an inventory for each in-scope system, and make it accessible to the response team even if the system itself is unavailable.
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- System name, owner, purpose, and business criticality.
- Model, product, or service provider; deployment location; and relevant version or configuration identifiers.
- Interfaces, APIs, tools, integrations, and credentials that connect the AI system to other services.
- Data sources and categories of information the system receives, stores, or produces.
- Logging locations, evidence-retention arrangements, and the people authorized to retrieve records.
- Upstream and downstream dependencies, including fallback processes and affected business operations.
- Provider incident contacts, escalation procedures, and relevant contract or service terms.
Keep the inventory current when systems or providers change. This inventory is an implementation approach drawn from NIST’s risk-management and AI-profile guidance; the preliminary NIST AI profile also emphasizes provider coordination and system-specific evidence during response.
3. Define what counts as an AI-related incident
Set criteria that fit your organization, and connect them to the existing incident-severity scheme. An AI-related report may involve a conventional cybersecurity event affecting an AI service, a concern about AI behavior, or an attack against an AI-enabled defensive capability. The examples below are scenarios to adapt, not an exhaustive official taxonomy.
- Suspected compromise of a model, AI service, account, or connected tool.
- Sensitive information exposed through an AI service or its associated records.
- Unexpected or harmful model behavior that affects business operations or users.
- An attack against an AI-enabled security or defensive system.
- Loss of an AI service that disrupts a critical process.
Define how staff and suppliers report concerns, who validates an initial report, and when it is escalated. NIST IR 8596 suggests separate categorization and defined triage and validation criteria for AI-related reports, as well as explainable escalation criteria for AI-enabled attacks.
4. Triage the report and assess impact
Give responders a consistent first-pass checklist. The goal is to establish what is known, what is uncertain, and which decisions cannot wait—not to assume that every unusual output is a security incident.
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- Validate the report using available records and the system owner’s knowledge; preserve relevant information before changing the system where practical.
- Identify affected models or services, versions, integrations, users, and business processes.
- Assess whether sensitive data, critical operations, or other systems may be involved.
- Estimate the affected period and scope, and note any uncertainty in those estimates.
- Assign severity and escalate under the organization’s criteria; record who made the decision and why.
NIST IR 8596’s preliminary draft identifies model integrity, exposure of sensitive data, and duration of model unavailability as factors to consider when estimating incident magnitude. Combine these with the organization’s existing measures of business impact rather than treating them as a replacement severity scale.
5. Preserve AI-specific evidence
Document what to collect, who can collect it, and where it will be stored. Preserve evidence in a way that maintains its integrity and records who accessed or changed it. Collect only what is appropriate under applicable privacy, security, retention, and legal requirements.
- Relevant prompts or other inputs and the corresponding outputs, where available and appropriate.
- Model and service versions, configuration, inference records, and model logs.
- Provenance data, such as records that help establish where relevant models or data came from.
- Account, credential, permission, integration, and configuration changes.
- Provider notices, support exchanges, and records of actions taken during the response.
NIST IR 8596 specifically identifies model logs, inference tables, and provenance data as potentially useful analysis artifacts. Availability and collection methods will vary by system and provider, so establish access arrangements before an incident.
6. Contain the incident with accountable decisions
Write playbooks for plausible scenarios and connect each action to an authorized decision-maker. Containment can reduce exposure but may also interrupt business operations or destroy information responders need. Define approvals and coordination steps in advance, especially where a service supports a critical process.
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- Isolate an affected application or integration from other systems.
- Revoke or rotate affected credentials, tokens, or keys.
- Disable a tool, API connection, or other capability implicated in the event.
- Switch to a documented manual or non-AI fallback process.
- Disable or roll back an AI component when the incident warrants it and the authorized owner approves.
For each action, specify who can approve it, who executes it, which stakeholders must be consulted, and how the decision is recorded. NIST’s general guidance supports defined authorities and prioritization; disabling or rolling back an AI module appears in the preliminary AI profile as a recovery consideration, not a universal requirement.
7. Coordinate with AI providers and other suppliers
Maintain current escalation contacts for model hosts, AI service providers, data providers, cloud providers, and other suppliers involved in the affected system. Assign an internal contact to communicate with each provider so responders do not send inconsistent requests through multiple channels.
Decide in advance what information to request, how evidence can be shared securely, how the provider will coordinate containment or restoration, and how updates will reach the incident commander. Check relevant contracts and service terms for available support, data access, and incident-coordination procedures. NIST IR 8596’s preliminary draft specifically discusses coordination with third-party AI service and data providers.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.8. Plan communications and assess notification duties
Set an internal escalation path for technical teams, affected business owners, executives, privacy and legal contacts, and communications staff. Identify who approves customer, partner, regulator, or law-enforcement communications where applicable. Keep messages factual, coordinated, and consistent with what the response team has verified.
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Maintain a separate legal and contractual notification matrix that reflects the organization’s jurisdictions, sector, affected data, and commitments. There is no universal notification deadline established by the sources used here: duties depend on the applicable law, regulation, contract, and incident facts. Have qualified legal or compliance personnel assess the relevant requirements; this plan is not legal advice.
9. Recover, validate, and learn
Set recovery criteria before they are needed. Identify who may approve restoration, what clean configurations or data are required, and how to verify that the cause of the incident has been addressed sufficiently for the service’s intended use. Depending on the incident, recovery may involve restoring a known-good configuration, rolling back a component, or considering retraining. Those AI-specific options are considerations in the preliminary profile, not steps required in every case.
Before returning a system to service, document the validation appropriate to its risks—for example, confirming access and configuration changes, checking that required integrations work, and confirming that the fallback can be withdrawn safely. Record the approval and any remaining risk accepted by the organization. Afterward, assign owners to convert lessons into changes to safeguards, monitoring, provider arrangements, response procedures, or staff training.
10. Exercise and maintain the plan
Exercise the procedures periodically, including the handoffs between security, system owners, operations, legal or privacy staff, communications, and providers. Tabletop scenarios can test decisions without requiring a live system change.
- A suspected data leak involving an AI service.
- A compromised provider, model, account, or connected tool.
- Unexpected or harmful output that affects a business process.
- An interruption to a critical process that relies on an AI service.
For each exercise, record decisions, missed or unclear handoffs, unavailable contacts, evidence gaps, and recovery bottlenecks. Assign an owner and due date to each improvement, then revise the relevant procedures and inventory. NIST recommends documenting procedures, testing or exercising them periodically, and using lessons to improve the broader cybersecurity risk-management program.
What to put in the plan itself
A compact, operational plan should let responders find the right action without searching through background material. Keep the following items together or link them through a clearly maintained internal index:
Quick Recap
- Scope, system inventory, severity criteria, and incident declaration authority.
- Role assignments, escalation contacts, decision approvals, and provider contacts.
- Triage and evidence-preservation checklists.
- Scenario playbooks for containment, fallback, and recovery.
- Internal communication paths and the separate legal and contractual notification matrix.
- Recovery validation criteria, exercise records, and improvement owners.
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