AI Quality and Risk Management Training programme

The AI Quality and Risk Management Training programme is a comprehensive, two-day, in-person training programme designed to equip executives with the knowledge and skills to effectively manage the quality and mitigate the risks associated with AI systems. This programme addresses the critical gap between classical and AI-specific risk and quality management in today's rapidly evolving technological landscape, focusing on application and alignment with relevant ISO/IEC/IEEE standards. Practical examples and demonstrations will prepare participants to readily apply the acquired skills in their organisation.

This training programme leverages AIQURIS - A TÜV SÜD venture's AI qualification platform, which operationalises the deep expertise in quality assurance and advanced AI risk management – backed by the consensus of international standards. Participants will learn how to cut through the complexity of real-world scenarios, building a real-world AI use-case during the training. Participants will gain confidence in identifying and transforming relevant requirements into actionable, effective mitigation strategies.

Course Content

Focusing on practical applicability, and providing executives with relevant frameworks to define robust strategies for ensuring quality and mitigating risks across all AI use cases, the course will cover the following topics:

Topic	Relevant Documents
AI System Life Cycle Management Understand roles, responsibilities and essential processes throughout the AI System Life Cycle	ISO/IEC 22989 – Terminology ISO/IEC 25059 – AI Quality Model ISO/IEC 5338 – AI Life cycle processes
AI System Risk and Quality Management Perform an AI Risk assessment and develop a Use-Case risk profile Plan, implement and continuously improve the effectiveness of an AI Quality Management system.	ISO/IEC 42001 – Quality management ISO/IEC 23894 - Risk management ISO/IEC 42005 – AI Impact Assessment
Data Governance Plan data governance processes throughout the data life cycle. Select relevant quality measures for a use case	ISO/IEC 8183 – Data life cycle ISO/IEC 5259 series – Data quality
Testing, Qualification and Supplier Management Develop requirements and assessment to qualify and accept an AI system. Setup essential processes to work with vendors, throughout procurement and contract monitoring.	ISO/IEC 17847 ISO/IEC 29119-11 IEEE 3119

Learning Outcomes

By the end of the training, attendees will gain:

• Comprehensive Knowledge: A thorough understanding of AI governance, AI lifecycle management, data governance, data quality management, AI testing and qualification, and AI supplier management, as well as insights into compliance requirements specific for AI systems.
• Hands-On Experience with AIQURIS Platform: Practical exposure to use tooling to cut through the complexity of real-world applications. Participants will build a use case directly on the AIQURIS platform, equipping them with skills to manage AI governance and quality within their own organisation.
• Certificate of Attendance: Each attendee will receive a Certificate of Attendance, validating their completion of the course and their acquired skills in AI quality management and governance.
• Certificate of AI Governance & Quality Management Capability: Each attendee who successfully completes the end of course assessment will be certified by AIQURIS, demonstrating their understanding of AI Quality and Risk and how they can apply it to their organisations.

Course Outline

Mode of delivery:

• 2 x 4 hours instructor led online sessions
• 8 hours of self-directed learning through online materials

Required materials:

• Computer with high-speed internet connection and webcam
• Microsoft Edge or Google Chrome
• [Optional] Microsoft Teams

Course Developer Profile

Dr. Martin Saerbeck, CTO and Co-Founder of AIQURIS

Dr. Martin Saerbeck brings over two decades of experience in AI, digital innovation, and risk management, specialising in building AI solutions that meet rigorous standards for safety, security, and compliance. As CTO and Co-Founder of AIQURIS, a TÜV SÜD Venture, he drives the mission to enable organisations to deploy AI in high-stakes environments with confidence. Dr. Saerbeck’s work has been instrumental in establishing the TÜV SÜD AI Quality Framework, which serves as a benchmark for AI auditing and certification across industries such as manufacturing, healthcare, and aerospace.

A recognised leader in AI standardisation, Dr. Saerbeck holds influential roles in organisations such as ISO/IEC, CEN/CENELEC, and IEEE SA, where he contributes to setting global standards for AI governance and risk management. He also draws on his extensive technical background, having led strategic R&D projects in AI, robotics, and IoT at TÜV SÜD and A*STAR Institute of High Performance Computing in Singapore. His academic credentials include a Ph.D. in Industrial and Product Design from Eindhoven University of Technology, a Master’s degree in Computer Science from Bielefeld University, and a Certificate of Excellence in Technology Strategy from UC Berkeley's Haas School of Business.

Dr. Saerbeck’s expertise in AI governance, technology strategy, and risk assessment equips participants with a deep understanding of AI quality assurance and the tools to design robust, compliant AI solutions.

Dr Cheng Yao, Senior AI Expert

Dr. Cheng Yao brings a decade of invaluable experience in the cybersecurity and AI sectors. She is a qualified TUV SUD AI Quality Trainer and a certified IEEE CertifAIEd Lead Assessor, specialising in assessing adherence to ethical criteria for AI systems. With a strong track record of academic publications in trustworthy AI technologies, she is also an active member of the Singapore Artificial Intelligence Technical Committee.

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