Set up one clear route for reporting AI-related incidents, assign people to assess and contain them, and keep a documented record through recovery and follow-up. The process should cover AI you build, buy, or use—including third-party systems—and make it possible to report a concern before its impact is fully known. NIST’s AI Risk Management Framework and the OECD’s 2025 common reporting framework can help shape that process; neither creates a universal legal reporting deadline.
What counts as an AI incident?
For internal reporting, define an AI incident broadly enough to capture an event or error involving an AI system that has caused, or could plausibly cause, harm or material disruption. Examples include discriminatory outcomes, privacy infringements, safety or security problems, and system errors that affect a business workflow or people relying on it. OECD identifies discrimination, privacy, safety, and security among the harms relevant to AI incident monitoring. (OECD: AI risks and incidents)
Do not make reporters decide whether an event meets a legal definition before they can report it. Your intake policy can accept incidents, errors, near misses, and uncertain events; the response team can classify them as information becomes available. Specify which internally developed, vendor-provided, and embedded AI systems are in scope, including the workflows in which they are used.
Assign ownership before an incident happens
Name a process owner accountable for maintaining the reporting route, escalation rules, and records. For each case, assign an incident lead who coordinates triage, response, updates, and closure. Identify backup decision-makers for absences and an executive escalation route for events that could affect safety, rights, essential services, or the organization’s ability to operate.
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Give responders clear authority to limit exposure while they investigate. Define who can restrict a feature, pause use, or roll back a release, and how urgent decisions are made when the usual approver is unavailable. Include supplier contacts and contingency steps for failures or incidents involving high-risk third-party AI systems. NIST’s AI RMF Core includes incident identification, response and recovery, and contingency planning for high-risk third-party systems. (NIST AI RMF Core)
Make reporting easy to find and safe to use
Choose a channel workers and other relevant reporters can locate quickly. It could be an internal form, shared mailbox, ticketing platform, or incident-management system; the sources do not prescribe one official product or intake channel. Publish the route where people encounter the systems, and provide an urgent alternative for situations where waiting could increase harm. Also provide a fallback if the primary channel is unavailable.
Tell reporters to preserve relevant information and avoid circulating sensitive data more widely than necessary. The OECD framework aims to support reporting by anyone while maintaining report quality, but it does not prescribe a particular form or tool. (OECD, Towards a common reporting framework for AI incidents)
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Compare channels against operational needs
| What to assess | Question to ask |
|---|---|
| Access and ease of reporting | Can the intended reporter groups find and use it, including when the event is urgent? |
| Routing and escalation | Can reports reach the right responder and on-call decision-maker based on severity? |
| Records and evidence | Does it preserve timestamps, decisions, evidence, and an auditable case history? |
| Privacy and security | Can access to sensitive prompts, outputs, logs, and affected-person information be appropriately controlled? |
| Coordination and review | Can it support supplier coordination, export case records, and help identify trends? |
| Ownership and fallback | Who maintains the channel, and what happens if it is unavailable? |
These are selection criteria derived from the lifecycle needs described by NIST and OECD, not a product ranking. A simple channel is useful only if reports are monitored, routed, and retained reliably.
Collect enough information to start a response
Keep the initial report short enough to complete when details are incomplete. Allow follow-up rather than making every field mandatory. A practical form can request:
- Reporter contact details, or a safe route for anonymous follow-up.
- AI system name, version or release, provider, deployment context, and affected workflow.
- When the event occurred and was detected, and what happened.
- Observed or plausible impact, who may be affected, and whether harm may be ongoing.
- Relevant prompts, outputs, logs, screenshots, or other evidence, handled under applicable privacy and security controls.
- Any immediate action already taken and whether the system remains in use.
This is a practical intake design synthesized from OECD’s flexible reporting aim and NIST’s monitoring and documentation outcomes; it is not a verbatim list of OECD’s 29 criteria. (OECD reporting framework; NIST AI RMF Core)
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Set severity rules and escalation routes
Write severity bands into organizational policy before a case arrives. The cited frameworks support managing varied risks, but they do not establish universal numeric severity thresholds or response clocks. Treat the bands below as a starting design, not as official NIST or OECD categories.
| Working category | Possible handling |
|---|---|
| Urgent or potentially severe | Escalate immediately to the designated incident lead and relevant decision-makers; consider containment while facts are checked. |
| Material but not apparently urgent | Assign an owner and route to the relevant safety, security, privacy, legal, product, or operations responders for assessment. |
| Low impact or informational | Record and assess through the normal workflow; escalate if new facts change the risk. |
| Unknown or uncertain | Keep the case open for assessment and route it for review when plausible impact could be serious; do not require proof of harm to raise concern. |
Assess actual and plausible impact, urgency, scope, reversibility, and exposure of safety, rights, privacy, security, or essential services. Define which functions must be brought in for each type of concern. Uncertainty should not silently downgrade a report.
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The incident lead should coordinate response and keep a timeline, decision record, and next-update plan. Depending on the risk, responders may restrict or pause the system, disable a feature, route work to a fallback, preserve relevant logs, or contact a supplier. Use pre-agreed triggers to escalate rather than relying on an individual’s intuition during a crisis.
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Decide who needs updates: affected people or communities, internal decision-makers, customers, suppliers, and authorities where applicable. Use approved communications that separate confirmed facts from open questions. NIST’s AI RMF Core says: “Manage 4.3: Incidents and errors are communicated to relevant AI actors, including affected communities. Processes for tracking, responding to, and recovering from incidents and errors are followed and documented.” (NIST AI RMF Core)
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Before restoring a system to normal operation, review whether the immediate risk has been addressed and what safeguards or approvals are needed. Record the incident, evidence, impact assessment, severity rationale, decisions, containment, investigation, communications and notifications, recovery, and corrective actions. Assign an owner and due date to each follow-up action.
Review incidents and near misses for recurring failure patterns. Feed findings into monitoring, testing, training, and system or workflow changes. NIST explicitly includes documented tracking, response, recovery, and communication; OECD describes monitoring as a way to build evidence and identify risk patterns. (NIST AI RMF Core; OECD: AI risks and incidents)
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When do you have to notify someone outside the organization?
There is no single deadline in the OECD framework that applies to every organization or AI incident. Published in 2025, the framework uses 29 criteria to help characterize incidents across contexts, identify high-risk systems, and assess risks and impacts; it is a benchmark designed to be adapted to domestic policy and legal frameworks, not a universal reporting duty. (OECD, Towards a common reporting framework for AI incidents)
For a real event, check the jurisdictions involved, your sector, your role in providing or deploying the system, the incident category, contracts, and applicable privacy, safety, product, and security notification obligations. Confirm any external reporting duties and deadlines with qualified internal counsel or compliance staff. Treat the AI incident process as an operational framework, not a substitute for jurisdiction-specific legal advice.
Use NIST and OECD as adaptable frameworks
NIST’s AI Risk Management Framework 1.0 is voluntary guidance for managing AI risks across design, development, use, and evaluation. Its four functions are Govern, Map, Measure, and Manage; the companion Playbook offers suggested actions to support them. NIST’s official page says the framework is being revised, so check that page for current version status when adopting it. (NIST AI Risk Management Framework; NIST AI RMF Playbook)
The OECD framework offers a cross-jurisdictional reference for consistent, interoperable incident reporting and monitoring. Use both as guidance for designing a workable process, while keeping organizational procedures and legal checks specific to your systems and operating context.
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