Lead Auditor ISO 42001 – AIMS

Overview

About ISO 42001:

The ISO 42001 AI Management System Lead Auditor course aims to equip participants with the knowledge and skills necessary to conduct effective audits of AI management systems and implement audit processes effectively within AI-powered organizations that support continuous improvement in accordance with this standard. The course covers the following topics:

Understanding the Standard Requirements:

This section aims to provide a comprehensive understanding of the standards to be audited:

Basic concepts and principles of an Artificial Intelligence Management System (AIMS)
Definition of the scope and importance of the standard within the context of an environmental management system
Detailed explanation of the standard’s requirements (e.g., context, leadership, planning, support, operation, performance evaluation, and improvement)
Introduction to ISO/IEC 42001: The purpose of an AIMS, its business benefits, and its relationship to other standards (e.g., ISO 27001)
Basic AI concepts and terminology: Understanding AI terminology and concepts as presented in ISO/IEC 22989
Ethical and legal principles: Understanding regulatory requirements and laws related to AI (e.g., the EU AI Act) and how to audit compliance with them
Process control and emergency preparedness and response

Implementing a Artificial Intelligence Management System

Identify internal and external issues, stakeholders, and their requirements.
The role of senior management in supporting the AI management system.
Identify and assess risks and opportunities, and establish objectives and policies.
Resources, competencies, awareness, communication, and document control.
Planning and controlling the operation of the AI management system.
Monitoring and measurement, internal audit, and management review.
Nonconformities, corrective actions, and continuous improvement.

Audit Principles and Guidelines

This section focuses on the methodological foundations of the audit process:

Definition and objectives of auditing.
Types of audits (system, process, compliance).
The seven principles of auditing according to ISO 19011.
Roles and responsibilities of auditors.
AI Impact Assessment audit: How to review the process of assessing the potential ethical, social, and legal consequences of using AI systems.
AI Risk Management audit: Verifying the identification, assessment, and mitigation of specific AI risks, such as bias, transparency, explainability, and accountability.

AI Reference Controls Audit:
AI Lifecycle Management.
Data Quality Management, Collection, and Use.
Security and Privacy Controls for AI Systems.
Communication with stakeholders regarding AI systems information.

Audit ethics (impartiality, objectivity, confidentiality). • Qualities of a successful auditor
Ethical conduct during an audit
Managing opening and closing meetings
Handling difficult cases during an audit

Auditor Competency and Requirements:

Develop the annual audit program for the AI management system.
Define the scope and objectives of the audit.
Organize the introductory meeting.
Conduct an AI system lifecycle audit: review the design, development, deployment, and deployment phases.
Assess the risks and impact of AI: audit how the organization conducts risk and impact assessments (social, ethical, and legal) of AI systems.
Conduct effective interviews with developers, compliance officers, and senior management.
Identify objective evidence-gathering techniques related to AI systems.
Ensure compliance and accountability: audit to ensure AI is used responsibly and ethically, and verify the implementation of controls related to transparency, fairness, and data management.