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1Fix the driver behind crashes, sound loss and screen glitches2Repair Windows errors before they cause bigger problems3Scan for outdated or missing drivers - takes under a minuteStop the agent first, preserve a read-only record of what happened, and put a qualified person in charge of the remedy. Revoke or narrow tool access, cancel queued work, and require approval before any further irreversible action. Then reconstruct the decision, protect affected people, determine reporting duties, correct the consequences, and restore autonomy only after controls are tested.
1. Contain the harm before investigating it
Treat a harmful action by an AI agent as an operational incident, not as an ordinary model-quality problem. Optimization can wait; the next automated call could make the damage wider or harder to reverse.
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Pause the agent and its automation
- Disable the agent’s scheduling, event triggers, message sending, purchasing, account-changing and other action capabilities.
- Stop queued jobs and revoke active sessions or tokens that could continue a workflow.
- Remove high-impact tools first. If a full shutdown would create a safety risk, move the system to a read-only or recommendation-only mode.
- Insert a human approval gate before every consequential action, including actions that appear to be routine retries.
- Name an incident lead with authority to stop systems, approve emergency changes and escalate outside the engineering team.
Do not let the agent decide whether it should remain active, classify its own incident, or approve its own correction. EU AI Act Recital 73 says assigned oversight personnel need the “necessary competence, training and authority” to perform that role, and that systems should have constraints they cannot override themselves.
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If the agent affects safety, access, money, employment, health, privacy or reputation, identify an immediate human safeguard. For example, suspend an automated denial while a trained reviewer checks the case, or block a payment workflow while finance staff verify the beneficiary. Record every emergency intervention and its time.
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2. Preserve evidence before rolling anything back
A rollback may remove the very state needed to explain the failure. Make a read-only copy before changing prompts, policies, models, integrations or data.
Capture the complete decision chain
- The user or event that triggered the run.
- System, developer and user instructions, including retrieved documents and conversation context.
- Model name, version, configuration, safety settings and policy version.
- Every tool call, argument, permission check, API response, retry and timeout.
- Human approvals, rejections, overrides, identities and timestamps.
- Accounts, roles, secrets, data sources and permissions available to the agent at the time.
- The agent’s output and the external effects: changed records, sent messages, transfers, access decisions or physical actions.
- Alerts, monitoring data, vendor notices and the time the problem was discovered.
Preserve the original state, not only a cleaned-up export. Hash or otherwise protect copies against silent alteration, restrict access to the incident team, and log every evidence access. Keep a separate working copy for analysis.
For covered EU high-risk deployments, Article 26 requires automatically generated logs to remain under the deployer’s control for at least six months. That is a minimum for the covered case, not a universal retention period for every system or jurisdiction. Other privacy, employment, financial, safety and cybersecurity rules may require a different period.
3. Reconstruct what happened
Build a timeline that another qualified reviewer can follow without relying on the agent’s explanation. A useful sequence is:
- Trigger: identify the event, request or sensor signal that started the run.
- Inputs: list the data actually supplied, including missing, stale or contradictory fields.
- Reasoning and output: record the model response and any policy or guardrail result. Do not treat a plausible explanation generated after the event as proof of the original reasoning.
- Execution: map each tool call to the permission that allowed it and the response it received.
- Approval: show whether a person reviewed the action, what information they had and whether they could stop it.
- Effect: document the external result, who was affected and whether the result is still changing.
- Discovery and containment: record when the issue was noticed, who acted and which controls stopped further effects.
Compare the observed path with the agent’s authorized purpose and least-privilege scope. A model can produce an incorrect answer without violating its instructions; a tool can execute a technically valid command that the agent was never meant to have. Those are different control failures and should be tracked separately.
4. Choose the response level using risk, not embarrassment
The right response depends on the consequences and the remaining uncertainty. Consider these axes together:
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| Question | Why it changes the response |
|---|---|
| How severe is the harm? | Safety, legal rights, access, money, privacy and reputation require progressively stronger escalation. |
| Can the outcome be reversed? | A reversible record change differs from a disclosure, physical injury or missed deadline that cannot be undone. |
| How many people were affected? | Wider impact calls for a broader freeze, coordinated communications and independent review. |
| Were affected people vulnerable? | Children, patients, employees, debtors and people dependent on essential services may need faster safeguards and specialist review. |
| How much autonomy and tool reach did the agent have? | Direct access to money, identity, production systems or physical controls raises the containment level even before the final harm is known. |
| How reliable is the evidence? | Missing logs, uncertain identities or changing vendor systems justify preserving more systems and involving independent investigators. |
| Are reporting triggers possible? | Contract, sector and jurisdiction rules can impose notice or cooperation duties. |
| How confident are you that containment worked? | If tokens, replicas, scheduled jobs or downstream automations remain active, keep the freeze broad. |
High severity, low reversibility, vulnerable or numerous affected people, broad tool access and poor evidence support an organization-wide pause of the affected workflow, an independent reviewer and early legal or regulatory escalation. A contained, reversible error with strong logs may permit a narrower suspension, but only after the incident lead verifies that no hidden execution path remains.
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5. Put a qualified human in charge of the remedy
Assign a reviewer who was not the sole designer or operator of the failed chain. The reviewer should have enough time, context, technical understanding and authority to correct the result.
Separate software rollback from human remedy
Rolling back a database, model or deployment may restore software state, but it does not automatically restore a person’s money, access, privacy or reputation. A deleted account can be recreated; a message sent to the wrong recipient cannot be unsent. For each effect, decide what practical repair is required and verify that it reached the affected person.
Create an appeal path
Give an affected person a clear route to challenge the outcome, reach a human and submit relevant information. The reviewer should record:
- the evidence considered;
- the decision to uphold, correct or reverse the outcome;
- any dissent or uncertainty;
- the action taken, its owner and its deadline; and
- how the person can escalate if the first review is disputed.
Do not send the appeal back through the same automated chain without an independent check. NIST’s post-deployment guidance expressly includes “appeal and override” alongside incident response, recovery, decommissioning and change management.
6. Contact affected people and assess reporting duties
When a person’s rights, safety, money, access or reputation may have been affected, communicate in plain language after the immediate facts are stable enough to avoid misleading them. Explain what happened in practical terms, what has been stopped, what correction is available, and how to reach a human reviewer.
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Do not promise that every affected person will receive the same remedy. Notice, restitution, regulator reporting and contractual disclosure depend on the system’s purpose, the harm, the country, the sector and the parties involved. Privacy, employment, consumer-protection, health, financial, safety and cybersecurity rules may apply simultaneously. Obtain qualified legal advice before deciding that no notice or report is required.
For covered high-risk AI deployments in the European Union, Article 26 requires deployers to use the system according to instructions, provide competent human oversight and monitor operation. The EU materials also require covered deployers to inform providers and authorities of serious incidents. Determine whether the event meets the applicable definition and deadline rather than applying that duty to every AI error.
If a vendor, processor, customer or public authority is part of the chain, notify it through the agreed incident channel while preserving your own evidence. Coordinate messages so that affected people receive a consistent account, but do not delay urgent protective action while negotiating wording.
7. Investigate the causes across the whole system
Most harmful outcomes are not explained by a single bad sentence from a model. Review the surrounding controls:
Data and retrieval
Check whether records were inaccurate, stale, incomplete, duplicated or drawn from the wrong person or tenant. Examine retrieval filters, ranking, permissions and document versions. Confirm that the agent did not treat an untrusted document or user instruction as a higher-priority policy.
Prompts and policies
Compare the instructions in production with the approved version. Look for ambiguous objectives, conflicting rules, missing refusal conditions, unsafe fallback behavior and incentives that rewarded speed or completion over caution.
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Model and integration behavior
Review model changes, fine-tuning, context limits, tool schemas, parser failures, retries, timeouts and vendor updates. Test whether a malformed or partial response could be interpreted as an approval or a completed action.
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Identity, secrets and permissions
Determine which identity executed each action and whether credentials were shared, overprivileged, expired or exposed. Rotate secrets that may have appeared in prompts, logs or tool responses. Verify that service accounts cannot reach unrelated systems.
Human approval and monitoring
Ask whether the reviewer saw the relevant evidence, had enough time, understood the risk and could actually stop the action. A “human in the loop” who merely clicks through an opaque recommendation is not meaningful oversight. Check alert thresholds, on-call coverage, audit visibility and whether earlier warnings were ignored.
Organizational incentives
Examine whether targets for automation, cost, speed or conversion discouraged escalation. NIST’s Generative AI Profile calls for trained incident-response personnel and procedures to communicate incidents and performance to downstream stakeholders. Assign those roles before the next deployment, not during the next emergency.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.8. Remediate the effects and the control failure
Use a written action plan with an owner and verification method for each item. Depending on the incident, actions may include:
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- correcting records, decisions and customer communications;
- returning funds, restoring access or repairing a service interruption;
- rotating exposed credentials and invalidating tokens;
- patching integrations, parsers and retry logic;
- reducing permissions and separating read, recommend and execute roles;
- requiring approval at defined risk thresholds;
- adding tests for adversarial inputs, missing data, prompt injection and tool failure;
- improving logs, alerts, dashboards and on-call procedures; and
- updating incident runbooks, training and contracts.
Test each correction against the original failure mode and plausible variants. A prompt edit is not evidence that the risk is fixed; demonstrate that the relevant tool is blocked, the reviewer is alerted and rollback or compensation works in practice.
9. Restore autonomy gradually
Keep the agent paused or in a lower-autonomy mode until corrective controls receive documented review. Before re-enabling an action, require:
- a defined authorized purpose and least-privilege permission set;
- successful tests covering the incident and foreseeable variations;
- named owners for operations, oversight and emergency shutdown;
- working logs that connect input, model, policy, approval, tool call and effect;
- live monitoring with alert recipients who can intervene; and
- a tested rollback and human-remedy procedure.
Start with a limited population, low-impact actions or recommendation-only output. Increase autonomy only when monitoring shows the controls work under real load. Define a stop condition in advance, and rehearse it. Restoration is a controlled change, not a declaration that the model is trustworthy again.
10. Use the governing frameworks as a practical checklist
The NIST AI Risk Management Framework (AI RMF) 1.0, published January 26, 2023, is voluntary and organized around Govern, Map, Measure and Manage. For an incident, that means assigning accountability, understanding the affected context, measuring system and control performance, then treating risk, responding, recovering and improving.
The EU AI Act is binding for covered uses and applies risk-based requirements for logging, documentation, human oversight, robustness and cybersecurity. The European Commission’s consolidated Article 26 text is current to July 27, 2026; its six-month log requirement applies to automatically generated logs held by covered high-risk deployers. Neither framework replaces sector-specific law or a qualified legal assessment.
Document which framework, contract or law supports each decision in the incident record. This makes the response auditable without pretending that a voluntary framework creates a universal legal deadline.
Quick Recap
Incident checklist
- Agent paused; queued jobs, tokens and high-impact tools stopped.
- Incident lead appointed with authority to intervene.
- Read-only evidence copy preserved before rollback or configuration changes.
- Timeline built from trigger through downstream effects and discovery.
- Severity, reversibility, scale, vulnerability, tool reach and reporting triggers assessed.
- Independent qualified human assigned to correction and appeals.
- Affected people protected and contacted when appropriate.
- Legal, contractual and regulator obligations assessed for the actual jurisdiction and sector.
- Root causes investigated across data, prompts, models, tools, identity, oversight, monitoring and incentives.
- Remediation verified with tests, monitoring, rollback and named ownership before autonomy returns.
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