ISO/IEC 42001 Artificial Intelligence Management System

Course Category : Risk Management

An advanced programme for developing institutional understanding of ISO/IEC 42001 requirements, AI governance, risk management, accountability, and continual improvement within a structured AI management framework.
Duration: 5 Days | Level: Advanced

Introduction

As organisations increasingly rely on AI-enabled systems and services, systematic AI management has become an important governance requirement. ISO/IEC 42001 provides a management-system framework through which organisations can establish accountability, address risks and opportunities, strengthen governance, and support responsible AI use.
This course examines the structure and principal requirements of an Artificial Intelligence Management System, covering organisational context, leadership, planning, support, operation, performance evaluation, and continual improvement. It also addresses AI risk management, impact assessment, governance responsibilities, and organisational controls to support structured alignment with ISO/IEC 42001..

Targeted Audience

  • Executives and managers responsible for AI governance
  • AI and Digital Transformation Managers and Specialists
  • Governance, Risk, and Compliance Professionals
  • Management Systems and Quality Professionals
  • Information Security and Data Protection Professionals
  • Internal Auditors and Assurance Professionals
  • Enterprise Risk Management Teams
  • AI and Technology Governance Consultants

Targeted Skills

  • Understanding ISO/IEC 42001 structure and requirements
  • Defining AIMS scope and organisational context
  • Establishing AI governance roles and responsibilities
  • Managing AI-related risks and opportunities
  • Understanding AI system impact assessment
  • Managing controls and documented information
  • Evaluating AIMS performance
  • Supporting continual improvement and audit readiness

Expected Outcomes

  • Interpret the principal requirements of an AI Management System under ISO/IEC 42001.
  • Define organisational context, interested parties, and AIMS scope.
  • Explain leadership responsibilities, policies, and AI governance roles.
  • Relate risks, opportunities, and impact assessments to planning and operation.
  • Identify relevant support, documentation, and operational control requirements.
  • Interpret monitoring, measurement, internal audit, and management review requirements.
  • Identify requirements for nonconformity management and continual improvement.
  • Support a structured organisational approach to ISO/IEC 42001 implementation readiness.

Training Topics Index

  • Purpose and principles of an Artificial Intelligence Management System
  • ISO/IEC 42001 structure and management-system approach
  • Understanding the organisation's internal and external context
  • Identifying interested parties, needs, and expectations
  • Defining the scope of the AI Management System

  • Leadership and commitment to the AI Management System
  • AI policy, organisational roles, responsibilities, and authorities
  • Identification and treatment of AI-related risks and opportunities
  • Establishing AIMS objectives and planning their achievement
  • Managing changes affecting the management system

  • AI risk assessment methodology
  • Risk treatment and selection of appropriate controls
  • AI system impact assessment concepts
  • Relationship between risks, impacts, and organisational controls
  • Documentation, oversight, and accountability for AI-related decisions

  • Resources, competence, and organisational awareness
  • Communication and documented information
  • Operational planning and control
  • Managing processes across the AI system lifecycle
  • Managing external parties and AI system or service suppliers

  • Monitoring, measurement, analysis, and performance evaluation
  • Internal audit requirements for the AI Management System
  • Management review and AIMS effectiveness
  • Nonconformities and corrective actions
  • Continual improvement and organisational readiness for assessment and certification

Course Features

  • Updated and Interactive Content
  • Hypothetical Examples and Case Studies
  • Pre- and Post-assessments to Measure Impact
  • Verified Certificate with a QR Verification Code