Boardroom Workshop: AI Governance

This workshop equips executives with practical guidance on navigating local and international AI regulations, assigning roles for AI risk and quality management, and making confident, defensible decisions. Participants will gain the insights needed to ensure AI initiatives are safe, compliant, and aligned with strategic business objectives.

Singapore is moving decisively towards global leadership in AI governance, with regulators and industry bodies placing corporate boards directly in focus. Whilst this training is anchored in the Singapore context, it recognises that Singapore is also playing an important role on the global AI stage – which is why we examine both local and international regulations, standards, and best practices.

Although Singapore has not yet enacted a binding AI law, it has established a robust foundation through the Model AI Governance Framework (2019, refreshed in 2020), the Personal Data Protection Act (PDPA), and initiatives under the AI Verify Foundation, including the 2025 Large Language Model Starter Kit. Together, these set clear expectations: boards and executives are accountable for responsible AI adoption, oversight, and assurance.

For the leadership of Singapore-listed companies and large enterprises, fiduciary duty now extends to understanding how AI is deployed across the business, ensuring risks are identified, controls are in place, and governance is demonstrable. With international regulation such as the EU AI Act coming into force in 2026, scrutiny on Singaporean companies operating globally will intensify.

This authoritative C-Suite AI governance training equips leaders with practical insights to navigate Singapore’s AI governance landscape, assign roles and responsibilities for AI risk and quality management, and make confident, defensible decisions on AI adoption.

Agenda

Boardroom AI Governance Workshop Agenda

Topic	Description
Opening & Context Setting (5 min)	AI risk management is no longer optional, boards are directly accountable Overview of recent developments and ongoing trends impacting Singapore’s AI ecosystem
Overview of AI Risks (10 min)	An introduction to the complex risk landscape of AI and consequences for the organisation Legal liability Reputational harm Financial loss Operational impact
Global AI Regulatory Landscape (10 min)	Singapore Model AI Governance Framework AI Verify Foundation 2025 LLM Starter Kit for safety testing MAS FEAT principles for AI in the financial sector PDPA obligations for data use NIST AI RMF (US): Influential and widely adopted best practice EU AI Act: Leading horizontally binding legislation Risk-based obligations for providers and deployers Requirements for AI literacy, transparency and code of conduct
What Accountability Means in Practice (15 min)	AI accountability and risk ownership: Roles of board, C-level executives and other stakeholders Singapore-listed company boards must demonstrate risk oversight under Model AI Governance Framework principles Practical implications: Deploying an AI recruitment tool scenario
AI Controls Checklist (10 min)	Introducing executive AI controls checklist AI governance requirements Use-case specific risk management Enterprise AI risk aggregation Monitoring, audits, and improvement plans Track organisation’s AI maturity
Wrap-Up and Next Steps (10 min)	Recap: AI accountability across the organisation Board training, AI literacy and risk awareness Leverage AI assurance platforms across the organisation Aggregate enterprise risk management

Meet the Course Developer

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 TUV SUD 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 TUV SUD AI Quality Framework, which serves as a benchmark for AI auditing and certification across industries such as manufacturing, healthcare, and aerospace.

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