ISO 42001 Artificial Intelligence Management System Internal Auditor Training

This course prepares participants to carry out internal audits of an AI management system against ISO/IEC 42001, using the auditing principles of ISO 19011.

It covers the audit programme, the practical business of gathering evidence about models, data and oversight, grading nonconformities, and reporting findings that lead to real correction rather than paperwork.

Objectives

• Apply ISO 19011 auditing principles to an AI management system
• Plan an audit programme and prepare risk-based audit checklists against ISO/IEC 42001
• Gather objective evidence about AI systems, data lineage, impact assessments and oversight
• Identify and grade nonconformities against clause requirements and Annex A controls
• Write clear findings and audit reports
• Verify corrective action and root cause analysis

Course outline

• ISO 19011 principles, audit types and the audit programme
• Clause-by-clause requirements of ISO/IEC 42001 from an auditor's view
• Auditing AI policy, roles and competence
• Auditing AI risk assessment and AI system impact assessment
• Auditing the Statement of Applicability and Annex A controls
• Auditing data provenance, quality and bias management
• Auditing transparency, human oversight and incident handling
• Auditing suppliers and third-party AI components
• Audit evidence, sampling and interview technique for technical teams
• Grading findings: major, minor, observation and opportunity for improvement
• Reporting, corrective action, root cause and follow-up

Who should attend

• Internal auditors adding AI to their scope
• Information security and privacy auditors
• AI, data and MLOps leads
• Compliance and risk professionals
• Management representatives for AI

Learning outcomes

Participants will be able to plan and lead an internal audit of an AI management system, produce defensible findings against ISO/IEC 42001, and verify that corrective actions address the underlying cause.