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Free AI Incident Response Plan Generator
Draft an incident response plan built for AI failures, biased output, data leakage through prompts, model errors, prompt injection, drift, and third-party model outages, using language aligned with the NIST AI Risk Management Framework 1.0 (MANAGE 4.3 and MANAGE 4.1) and ISO/IEC 42001. Answer a short guided form, generate the plan, then download it as Word or PDF. It is free and needs no sign-up. Your details are processed securely to write the plan and are never stored, sold, or used for training.
Plan details
Fill in your organization details and the AI systems in scope. You get a complete AI incident response plan, with incident types, severity tiers, response phases, roles, and notification, ready to download as Word or PDF.
Organization
Scope
Ownership & severity
Notification
Your plan will appear here. Fill in the details on the left and select Generate plan.
An AI incident response plan is a written procedure for detecting, containing, and recovering from failures specific to AI systems, such as harmful output, data leakage through prompts, a model error driving a wrong decision, prompt injection, drift, or a third-party model outage. This free tool generates one from a short form, incident definitions, severity tiers, response phases, roles, and notification, as Word or PDF, with no paywall and no sign-up.
How the AI incident response plan generator works
01
Describe your AI systems
Enter your organization, the systems in scope, the incident owner, a severity scheme, and whether to include a regulator-notification step.
02
Generate your plan
The tool writes a plan from your details, with AI-specific incident types, severity tiers, response phases, roles, and notification, aligned with the NIST AI RMF 1.0 and ISO/IEC 42001. Results come back in seconds.
03
Download and review
Export the plan as a PDF or an editable Word file, then have it reviewed by your security, legal, and compliance leads before you rely on it.
Free, private, and built on NIST AI RMF 1.0 and ISO/IEC 42001
Most incident-response templates sit behind a lead form or ignore AI failures entirely. This one asks for no sign-up and keeps nothing. Writing a plan needs a language model, so your details are sent to our server and processed there, then discarded. The plan is structured around the NIST AI Risk Management Framework 1.0, MANAGE 4.3, which calls for incident response and recovery for AI, and MANAGE 4.1, which calls for the monitoring that detects incidents and feeds the lessons back, and is worded to line up with the operational-control requirements of ISO/IEC 42001. When you enable the notification step, it references GDPR breach-notification timing generically. We built this from our own AI governance programme, not from a summary of the standard: see BlockSurvey's AI Policy for how we apply the same practices to ourselves.
01
Processed, never kept
Your details are processed securely to write the plan and are never stored, sold, or used for training. Keep the form to organization-level details and leave secrets, personal data, and PHI out.
02
No account required
No sign-up, no email wall, no tracking of the systems you plan for.
03
Free, real download
The complete plan as Word or PDF at no cost, not a watermarked sample.
What the plan includes
Eight sections, structured around the NIST AI RMF 1.0 MANAGE function:
- Header and scope, organization, preparer, effective date, and the AI systems the plan covers.
- What counts as an AI incident, six common types, each tagged MANAGE 4.3: harmful or biased output, data leakage through prompts, model error causing a wrong decision, prompt injection or abuse, model drift, and third-party model outage.
- Severity classification, a 3-tier or 4-tier scheme with criteria for each tier.
- Response phases, detect, triage, contain, eradicate, recover, and review, adapted to AI failures.
- Roles and responsibilities, the incident owner, the response team, and the reporter.
- Notification, internal escalation, affected-user handling, and an optional regulator / GDPR breach-notification step.
- Post-incident review and lessons learned, turning each incident into monitoring and guardrail changes (MANAGE 4.1).
- A counsel-review disclaimer carried inside the document itself.
AI incidents vs traditional IT incidents
Your existing IT incident process assumes something is down, breached, or misconfigured. AI failures often happen while everything is technically running, which is why they need their own detection and containment steps.
| Traditional IT incident | AI incident | |
|---|---|---|
| Typical trigger | Outage, intrusion, misconfiguration, or data loss. | Biased or harmful output, data leaked through a prompt, a wrong automated decision, or model drift. |
| Visibility | Usually loud, alerts, errors, downtime. | Often silent, the system runs fine but produces the wrong result. |
| Detection | Uptime and security monitoring. | Output review, drift and quality metrics, and user reports (MANAGE 4.1). |
| Containment | Isolate, patch, or restore the system. | Disable the model, fall back to human review, or block the abusive input. |
| Recovery goal | Restore service and uptime. | Restore trustworthy behaviour and re-review affected decisions (MANAGE 4.3). |
Built for every team working with AI
Whether you ship models or just rolled out your first AI assistant, someone will ask what you do when it goes wrong. This plan gives you a dated, structured answer, and it pairs well with an AI survey platform when the data you feed those systems comes from people.
01
Compliance & privacy teams
Show a documented AI incident procedure, not a promise to figure it out later.
02
Legal & risk
Tie AI failures to notification duties and keep the decisions on record.
03
Product & engineering
Know exactly how to disable, fall back, and recover before an incident, not during one.
04
Security teams
Extend your IR runbook to prompt injection, data leakage, and model abuse.
05
Startups adopting AI
Answer enterprise AI questionnaires with a real plan instead of a blank.
06
Vendors selling into enterprise
Give buyers evidence that you manage the AI in your product responsibly.
Your plan flags data leakage as an AI incident.
Two incident types your plan flags, data leakage through prompts and third-party model outages (MANAGE 4.3), start with the data you feed those systems. BlockSurvey is an AI survey platform, encrypted end to end, with a published AI policy you can cite in your own vendor assessment, so responses are never sold, mined, or used to train models.
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Frequently Asked Questions
- An AI incident response plan is a written procedure for detecting, containing, and recovering from failures that are specific to AI systems, such as harmful or biased output, data leakage through prompts, a model error that drives a wrong decision, prompt-injection abuse, model drift, or the outage of a third-party model. This free tool generates one for you from a short guided form: it defines what counts as an AI incident, sets severity tiers, lays out the response phases from detect to review, names the owner and team, and adds a notification step, all aligned with the NIST AI Risk Management Framework 1.0 and ISO/IEC 42001.