Required documentation for an AIMS

A practical way to understand ISO 42001 documentation requirements is to think in three layers: high-level governance documents, operational procedures and lifecycle documentation, and ongoing records or evidence. Together, these layers show intent, execution, and continuous oversight of AI systems. 1) Governance and scope documentation This layer defines the organization’s overall approach to AI governance and establishes accountability at the highest level.

• AI management system policy: The AI management system policy is a document that states why the organization uses AI, the objectives of the AIMS, and the principles that guide AI use, such as fairness, transparency, safety, and accountability. It also demonstrates management commitment to responsible AI governance.
• Scope and context of the aims: This documentation clearly defines the scope of the AIMS. It explains which AI systems, products, services, business units, and locations are included and which are excluded, along with the justification for each exclusion. It also identifies interested parties, such as customers, regulators, employees, and partners, along with their expectations related to AI use.
• Roles, responsibilities, and organization structure: ISO 42001 requires clarity on who is responsible for AI governance. This includes defining roles such as the AIMS owner, AI risk owners, product owners, data protection officers, security leads, and oversight committees. An organization chart or responsibility matrix is often used to show how these roles interact.

3) Records and evidence for audits This layer shows how AI risks are identified, managed, and controlled throughout the AI lifecycle.

• AI risk assessment methodology and risk register: organizations must document how AI risks are assessed, including risk criteria, impact definitions, and likelihood scoring. The risk register records identified AI risks, their potential impacts, and treatment measures such as controls, mitigations, or acceptance decisions.
• Statement of applicability and AI controls catalogue: The statement of applicability documents which Annex A controls apply to the organization, which are excluded, and why. It also records implementation status and links each control to supporting evidence. This document is central to certification audits.
• Policies and procedures: Operational policies and procedures define how AI systems are built, deployed, and managed. These typically include AI development and deployment procedures, data governance policies, model validation and testing processes, human oversight rules, incident response procedures, third-party AI management, and change management controls.
• AI system inventory and lifecycle documentation: organizations must maintain an inventory of AI systems and use cases. Lifecycle documentation includes design decisions, training data sources, model versions, deployment dates, monitoring plans, and decommissioning records. This ensures traceability from design through retirement.

2) Risk, controls, and lifecycle documentation This layer provides proof that the AIMS is operating as designed and is essential during audits.

• Risk and impact assessment records: These include completed AI risk assessments, AI impact assessments, and documented risk treatment decisions.
• Monitoring and performance logs: Organizations must retain evidence of ongoing monitoring, such as accuracy metrics, drift detection results, bias analysis, system uptime, and alerts.
• Training and competency records: Training records show that staff involved in AI development, deployment, and governance are competent and aware of relevant risks, policies, and responsibilities.
• Audit, review, and incident records: This includes internal audit reports, corrective action records, management review minutes, AI incident and complaint logs, post-incident analyses, and evidence of improvements made.
• Certification and external audit reports: Certification decisions, surveillance audit reports, and recertification results form part of the official compliance record.

In practice, many organizations use templates and governance, risk, and compliance platforms to centralize this documentation and make audits and change management more efficient.