AIQURIS-ai-quality-and-risk-compliance-and-assurance-training

AI Quality and Risk Management Training

Build practical expertise to manage AI risks, ensure quality, apply ISO/IEC standards, and lead responsible, compliant AI initiatives with confidence using real-world cases and the AIQURIS platform.

Artificial Intelligence is transforming industries and redefining accountability. Yet many organisations still rely on governance models built for traditional IT systems, which cannot fully address AI’s unique risks, standards, and lifecycle demands. This two-day training, delivered by Singapore’s leading AI experts who actively shape international standards, equips executives and teams with the frameworks, hands-on tools, and practical techniques needed to lead AI initiatives confidently, responsibly, and at scale.

Training Overview

This two-day AI training programme gives executives and teams the tools to manage AI risks, ensure quality, and meet regulatory expectations across the AI lifecycle. Available both online and in person, the training bridges the gap between traditional governance methods and the specific challenges of Artificial Intelligence.

 

The course combines theory, real-world use cases, and practical application using the AIQURIS platform. Participants learn how to apply leading standards such as ISO 42001 and ISO 23894 to their own AI use cases and governance structures.

Learn Directly from Leading Experts

Dr Martin Saerbeck, CTO and Co-Founder of AIQURIS

Dr 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. His work has been instrumental in establishing the TÜV SÜD AI Quality Framework, now a benchmark for AI auditing and certification across industries such as manufacturing, healthcare, and aerospace.

Dr Yao Cheng, Principal AI Expert

Dr Cheng brings a decade of experience in cybersecurity and AI. She is a qualified TÜV SÜD 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 research in trustworthy AI technologies, she is also an active member of Singapore’s Artificial Intelligence Technical Committee.

Key Concepts

Gain hands-on experience with real-world AI quality and risk management techniques. Learn how to apply ISO and IEC standards to governance, data, and supplier evaluation.

AI Standards Table - Mobile Responsive
Topic Relevant Standards
AI System Life Cycle Management

Understand roles, responsibilities and essential processes throughout the AI system lifecycle

  • 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. Set up essential processes to work with vendors, throughout procurement and contract monitoring.

  • ISO/IEC 17847
  • ISO/IEC 29119-11
  • IEEE 3119
AI Standards Table - Mobile Responsive
Topic Relevant Standards
AI System Life Cycle Management

Understand roles, responsibilities and essential processes throughout the AI system lifecycle

  • 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. Set up essential processes to work with vendors, throughout procurement and contract monitoring.

  • ISO/IEC 17847
  • ISO/IEC 29119-11
  • IEEE 3119

What You’ll Gain

  • Comprehensive Knowledge:
    You will understand how to manage AI governance, risk, data quality, testing and supplier collaboration.
  • Hands-On Experience with AIQURIS Platform: 
    You will apply your knowledge directly by building a use case using the AIQURIS platform.
  • Certificate of Attendance:

    All participants receive a Certificate of Attendance validating their completion of the course.

  • Certificate of AI Governance & Quality Management Capability: Each attendee who successfully completes the final assessment will be certified by AIQURIS, demonstrating their understanding of AI Quality and Risk and how they can apply it to their organisations.

Who Should Join

This programme is designed for professionals ready to take AI from policy to practice:

  • CIOs, CDOs and Heads of AI
  • AI governance leads, compliance officers and risk managers
  • Technical teams including data scientists and ML engineers
  • Procurement and vendor managers

Practical Training Set-up

Mode of delivery

  • Instructor-Led Online Sessions: 2 sessions of 4 hours each, interactive and practical

  • Self-Directed Learning: 8 hours of guided online materials to reinforce concepts

 

What You’ll Need

  • Computer with high-speed internet and a webcam

  • Microsoft Edge or Google Chrome

  • Optional: Microsoft Teams for live collaboration

 

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