ISO/IEC 42001 Artificial Intelligence Management System — Lead Auditor Training Course

The ISO/IEC 42001 Lead Auditor Training Course equips professionals with the knowledge and skills required to perform audits of Artificial Intelligence Management Systems (AIMS) based on ISO/IEC 42001. This course provides an in-depth understanding of auditing processes, techniques, and best practices, preparing participants to conduct first, second, and third-party audits in accordance with ISO 19011 and ISO/IEC 17021-1.

Key Learnings

Upon completion of this course, participants will:

Explain the fundamental concepts and principles of an AI management system based on ISO/IEC 42001
Interpret the ISO/IEC 42001 requirements for an AI management system from the perspective of an auditor
Evaluate the AI management system conformity to ISO/IEC 42001 requirements in accordance with the fundamental audit concepts and principles
Plan, conduct, and close an ISO/IEC 42001 compliance audit, in accordance with ISO/IEC 17021-1 requirements, ISO 19011 guidelines, and other best practices of auditing
Manage an ISO/IEC 42001 audit program

Course Content

Module 1: Introduction to ISO/IEC 42001 and Artificial Intelligence Management Systems

Overview of Artificial Intelligence (AI) and its impact on industries
Understanding ISO/IEC 42001 standard requirements
Key components of an Artificial Intelligence Management System (AIMS)
Introduction to AI ethics, governance, and risk management frameworks
Purpose and benefits of ISO/IEC 42001 certification

Module 2: Fundamental Audit Concepts and Principles

Overview of audit standards: ISO 19011 and ISO/IEC 17021-1
Auditing principles: impartiality, confidentiality, and due diligence
Types of audits: first-party, second-party, and third-party audits
Overview of AIMS auditing process: planning, conducting, reporting, and follow-up

Module 3: Preparation for the ISO/IEC 42001 AIMS Audit

Understanding the audit lifecycle: audit scope, objectives, and criteria
Audit planning: resources, time management, and documentation review
Risk-based auditing in AI systems
Developing checklists and audit questionnaires for AIMS
Pre-audit preparations and team assignments

Module 4: Conducting the Audit

Opening meetings: establishing communication and defining audit scope
Interviewing and gathering evidence from AI system stakeholders
Auditing key areas: data governance, risk management, ethics, compliance
Sampling techniques and audit data collection methods
Managing audit team members and dividing responsibilities
Recording audit observations and findings

Module 5: Reporting the Audit Findings

Preparing the audit report: format and structure
Writing non-conformities, observations, and areas for improvement
Classifying audit findings based on ISO/IEC 42001 compliance
Conducting the closing meeting: presenting findings and recommendations
Follow-up and corrective actions for non-conformities
Ensuring continuous improvement in AIMS

Module 6: Lead Auditor Responsibilities and Managing the Audit Program

Role and responsibilities of the lead auditor
Managing the audit team and resolving conflicts
Ensuring consistency and integrity throughout the audit process
Conducting follow-up audits and verifying corrective actions
Continuous monitoring and improvement of audit processes
Case studies: Real-world scenarios of AI system audits

Who Should Attend?

This training course is intended for:

Individuals with a background in auditing, whether internal or external, seeking to specialize in auditing AI management system
Managers or consultants seeking to master the AI management system audit process
Individuals responsible for maintaining conformity with the AI management system requirements in an organization
Expert advisors in AI management
Professionals involved in analyzing and understanding business requirements for AI implementation
Individuals involved in the development and implementation of AI solutions and in designing the architecture of AI systems

Career Path