ISO 42001 A.9.2: AI Incident Recording and Reporting
ISO 42001 A.9.2 requires organizations to document and track AI-related incidents, near-misses, and adverse outcomes—creating an audit trail that demonstrates accountability and continuous improvement. For SMBs deploying AI systems, incident recording isn't just compliance; it's the foundation of safe, trustworthy AI operations. Without a structured process, security gaps and system failures go undetected.
What this means
This control mandates that your organization establish a comprehensive incident recording system for all AI-related events. You must capture incident descriptions, identify which AI systems were affected, assess business and safety impacts, conduct root cause analysis, and document corrective actions. Incidents deemed significant must be escalated to relevant internal stakeholders and, where legally or contractually required, reported to external authorities. The goal is to create an auditable record that shows how your organization identifies, responds to, and learns from AI failures.
How to comply
- 1.Define what qualifies as an AI incident, near-miss, or adverse outcome (e.g., model errors, security breaches, data quality failures, unintended outputs)
- 2.Create a standardized incident report template capturing description, affected AI systems, impact assessment, root cause, and corrective actions
- 3.Establish a centralized incident logging system accessible to relevant teams (security, data, ML, compliance)
- 4.Develop criteria for determining significance and escalation thresholds for internal and external reporting
- 5.Assign clear ownership for incident investigation and corrective action follow-up
- 6.Set retention policies for incident records (typically 3–7 years depending on jurisdiction)
- 7.Define notification procedures and timelines for reporting to stakeholders and external authorities
- 8.Conduct periodic reviews of incident records to identify patterns and systemic improvements
Evidence auditors look for
- Incident log with at least 10 documented AI-related incidents showing description, system, impact, root cause, and corrective action
- Incident report template used across the organization for consistency
- Evidence of escalation and communication to internal stakeholders (email, meeting minutes, Slack threads)
- Documentation of corrective actions implemented and their effectiveness verification
- Records of external reporting (to regulators, customers, or affected parties) where required
- Incident review meeting notes showing analysis of trends and preventive measures
- Signed acknowledgments from responsible parties confirming closure and action completion
Frequently asked questions
When will FAQs be available?
The FAQ for this control is currently being prepared.
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