AI Incident Management Policy Template

Establishes procedures for detecting, reporting, investigating, and remediating incidents related to AI system failures, unintended behaviors, or harmful outcomes. (ISO/IEC 42001: Clause 10 — Improvement)

What This Policy Covers

Purpose and Scope-Policy objectives and definition of AI-related incidents.

AI Incident Classification-Severity levels and AI-specific incident categories: model failure, bias, adversarial attacks, data issues.

Incident Detection and Reporting-Detection mechanisms, reporting channels, and initial triage procedures.

Investigation and Root Cause Analysis-Investigation methodology, evidence collection, and root cause determination.

Containment and Rollback Procedures-Model rollback, traffic redirection, fallback mechanisms, and system isolation.

Stakeholder Notification-Internal escalation paths, affected party notification, and regulatory reporting obligations.

Corrective and Preventive Actions-Remediation planning, implementation tracking, and effectiveness verification.

Lessons Learned and AIMS Integration-Post-incident review, knowledge base updates, and AIMS improvement inputs.

Required Sections

A compliant AI Incident Management Policy for ISO 42001 must include the following8 sections. Each section addresses a specific control requirement that auditors will review.

Purpose and Scope

Policy objectives and definition of AI-related incidents.

AI Incident Classification

Severity levels and AI-specific incident categories: model failure, bias, adversarial attacks, data issues.

Incident Detection and Reporting

Detection mechanisms, reporting channels, and initial triage procedures.

Investigation and Root Cause Analysis

Investigation methodology, evidence collection, and root cause determination.

Containment and Rollback Procedures

Model rollback, traffic redirection, fallback mechanisms, and system isolation.

Stakeholder Notification

Internal escalation paths, affected party notification, and regulatory reporting obligations.

Corrective and Preventive Actions

Remediation planning, implementation tracking, and effectiveness verification.

Lessons Learned and AIMS Integration

Post-incident review, knowledge base updates, and AIMS improvement inputs.

Generate a Customized Version

This template shows the required structure. PoliWriter generates a fully customized AI Incident Management Policy that references your actual cloud providers, identity systems, tools, and team practices — ready for auditor review.

Generate Customized AI Incident Management Policy

Policy Details

Framework

ISO 42001

Other ISO 42001 Templates

AI Management System Policy

Establishes the overall AI management system (AIMS) including leadership commitment, AI principles, and organizational context for responsible AI development and deployment. (ISO/IEC 42001: Clause 5 — Leadership)

AI Risk Management Policy

Defines the risk management framework for identifying, assessing, treating, and monitoring risks associated with AI systems throughout their lifecycle. (ISO/IEC 42001: Clause 6.1 — Actions to address risks and opportunities)

AI Data Governance Policy

Governs the acquisition, preparation, quality, lineage, and lifecycle management of data used in AI systems to ensure trustworthy AI outcomes. (ISO/IEC 42001: Annex A — A.10 Data for AI Systems)

AI Impact Assessment Policy

Establishes the process for conducting impact assessments on AI systems to evaluate potential effects on individuals, groups, and society. (ISO/IEC 42001: Annex A — A.3 AI System Impact Assessment)

AI Transparency & Explainability Policy

Ensures AI systems operate transparently with appropriate levels of explainability for stakeholders, regulators, and affected individuals. (ISO/IEC 42001: Annex A — A.5 Transparency and Explainability)

Human Oversight of AI Systems Policy

Defines requirements for human oversight, intervention capabilities, and accountability structures for AI system operations. (ISO/IEC 42001: Annex A — A.7 Human Oversight)

AI Monitoring & Evaluation Policy

Defines requirements for continuous monitoring, performance evaluation, and periodic auditing of AI systems in production. (ISO/IEC 42001: Clause 9 — Performance Evaluation)

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