Control · C-003 · Monitoring, Assurance & Incidents
AI incident response and rollback
When an AI system fails or produces harmful output, a defined procedure contains it, restores a known good state, preserves the evidence and manages the consequences.
- Control type
- Corrective
- Risks addressed
- 8
- Audience
- Heads-of · Practitioner
- Frameworks
- Article 17 · Article 20 · MANAGE 4
- Responsible AI domain
- Lifecycle stage
- Reviewed
- 2026-11-11
What it does
It limits the harm from an AI failure once the failure is known. The procedure covers who declares an incident and takes charge, how the system is contained, whether by disabling a feature, switching to the fallback or reverting to an earlier version, how evidence is preserved, and how affected people, the business and regulators are informed. The incident manager runs the response and the system owner is accountable for the system. It operates whenever monitoring, a report or a complaint reveals a failure.
How to implement it
- Bring AI incidents into the organisation's incident process, with clear criteria for declaring one.
- Keep earlier versions of model, prompt and configuration ready to redeploy.
- Rehearse containment and rollback, including out of hours.
- Preserve logs, versions and outputs before changing anything.
- Assess reportability early, and scope customer impact from decision records.
- Close with a review, and do not restore the system until the cause is understood.
Evidence it operates
Design: an incident procedure covering AI; rollback instructions for each system. Operation: incident records with timeline and decisions; a rollback rehearsal or real use; preserved evidence; post-incident reviews and completed actions.
Where it fits
After detection. It is the primary control for AI incident response gap and, with the stop mechanism, for inability to stop or roll back AI. It uses AI incident classification and playbooks for the specifics, and hands over to regulatory incident notification and customer remediation for AI errors.
Limits
It starts only when someone recognises an incident. A hosted model cannot be rolled back by the customer, and an agent's completed actions may not be reversible. Rolling back removes the fix as well as the fault if the earlier version had problems of its own.
Risks this mitigates
Primary mappings
- AI incident response gap High
- Provides the response and rollback capability. AI-specific failures are not covered by the incident process: they have no classification, no playbook and no trained responders.
- Inability to stop or roll back AI High
- Maintains the ability to revert to a known good version. A misbehaving system cannot be disabled, reverted to a known good version, or have its actions reversed quickly enough to limit harm.
Supporting mappings
- AI model drift and degradation High
- Reverts or withdraws a degraded model. A deployed model's performance declines as the world it operates in moves away from the data it was trained and validated on, with no change to the model itself.
- Model backdoors and trojans Critical
- Reverts to a known good model when tampering is found. A model contains a hidden behaviour that an adversary can activate with a trigger known only to them, while the model behaves normally on all other inputs.
- Third-party model and dataset provenance Medium
- Removes a component found to be compromised. A model, dataset or component is adopted from an external source with no verified account of where it came from, how it was made, what rights attach to it or how it has changed.
- Training data bias and discriminatory outcomes High
- Withdraws or reverts the system when discriminatory outcomes are found. Bias in the data a model learns from, whether from history, sampling or labelling, is reproduced or amplified in its outputs and in the decisions that rely on them.
- Uncontrolled AI change High
- Reverts a change that causes harm. Models, prompts, data sources and configuration change in production without assessment, testing, approval or a record.
- Untested AI failure scenarios Medium
- The response and rollback process is what the exercise rehearses. Scenario testing does not include AI-specific disruption, so the organisation does not know whether it could stay within tolerance if its AI failed.
Framework and clause references
| Framework | Clause | Title |
|---|---|---|
| Digital Operational Resilience Act (DORA) | Article 17 | ICT-related incident management process Incident management process. |
| EU AI Act | Article 20 | Corrective actions and duty of information Corrective action and withdrawal. |
| NIST AI Risk Management Framework (AI RMF 1.0) | MANAGE 4 | Risk response, recovery and communication plans are documented and monitored Response and recovery. |
Related terms
How to cite
Axiom Verity (2026). AI incident response and rollback. Reference Library, C-003. https://axiom-verity.com/controls/incident-response-and-rollback. Reviewed 2026-11-11.
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