Auditor/Lead Auditor Training on Artificial Intelligence Management System based on ISO/IEC 42001:2023

Qualifying People - Developing Future

Qualifying People - Developing Future


In this course, participants will develop the competence to master a model for auditing artificial intelligence risk management processes throughout their organisation using the ISO/IEC 42006:2024 standard (in FDIS currently) as a reference framework. Based on practical exercises and discussions, participants acquire the necessary knowledge on the practical application of the standard and learn how to meet the requirements specified in the standard. The delegates will develop skills to audit an AIMS based on ISO/IEC 42006 (currently in DIS stage) standard.

Duration: 5 - day course
Language: English




At the end of the course, participants will be able to:

  • Understand the basics of AI and ML
  • Understand the framework and apply the standard for managing risk and opportunities
  • Demonstrate responsible use of AI
  • Establish traceability, transparency and reliability
  • Enable cost savings and efficiency gains


Topics to be covered in this course include:

  • What is Artificial Intelligence (AI)?
  • What is Machine Learning (ML)?
  • The concept of data science
  • AI concepts and terminologies
  • How AI becomes disruptive, Gen AI and discriminative AI Regulatory stipulations, transparency needs
  • Ethical use of AI
  • What is the ISO/IEC 42001:2023 standard?
  •  Applicability of the standard
    • Benefits
    • Responsible use of AI Efficiency factors
    • Risk-based approach traceability, transparency and reliability
    • Clauses and requirements
  • ISO 22989:2022 standard
  • ISO/IEC 23053:2022 standard - Framework for Artificial Intelligence (AI) Systems Using Machine Learning (ML)
  • ISO/IEC 23894:2023 standard - Artificial intelligence - Guidance on risk management
  • Case studies and exercises
  • Introduction to ISO/IEC 42006:2024 (Currently in DIS stage)
  • Auditing principles
  • Conflict of interest
  • Structural requirements
  • Resource requirements for conducting AI audits
    • For application review
    • For audit report review
    • For making certification decisions
    • For making decisions on appeals
  • Information requirements
    • AIMS certification documents
  • Process requirements
    • Audit programme
    • Audit methodology
    • Audit time
    • Sampling
    • Combined audit
  • Audit planning
    • Audit objectives
    • Audit criteria
    • Audit plan for AIMS
  • Initial certification
    • Stage 1 audit
    • Stage 2 audit
  • Conducting audits
    • Specific elements of AIMS audits
    • Audit reporting
  • Certification maintenance
  • Surveillance audits
  • Recertification audits
  • Special audits


Participants will learn through lectures, case studies, group exercises and discussions.



This course is specially designed for:

  • Management system auditors
  • Risk managers (ERM or Infosec/AI RM) Executive level stakeholders – CEO, CFO, HR Head, CTO, CIO
  • Business Process Owners, Business Finance Managers, Business Risk Managers Regulatory Compliance Managers, Business Function Managers
  • AI Developers, AI Operators
  • Quality Managers
  • Business Excellence Professionals, Information Security Professionals Consultants
  • AI Service Vendors
  • AI process practitioners
  • AI Project Managers
  • AI architects
  • Information security managers
  • Any AI Stakeholder, in any manner
  • Management System Auditors

Prerequisite: Any Management System LA certificate and an understanding of data analysis, data science concepts


The course content and structure are designed by the domain experts from TÜV SÜD.
With immense experience and knowledge in the relevant standards, our team of product specialists and technical experts at TÜV SÜD, developed the course content based on current business landscape and market requirements.


  • What are the benefits of enrolling in this course?
    • Get introduced to the basics of AI and ML
    • Enable cost savings and efficiency gains
    • Discover how to establish traceability, transparency and reliability
    • Understand the various aspects involved in AIMS audits
    • Learn how to perform effective audits to ensure a robust AIMS
    • Know how ISO/IEC 42001 can enable responsible use of AI within organisation


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