Executive Workshop on 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 advancing rapidly towards global leadership in AI governance, with regulators and industry bodies placing boards and executives directly in focus. While this training is grounded in the Singapore context, it also addresses the broader international AI landscape, covering local and global regulations, standards, and best practices.

Although Singapore has not yet enacted binding AI legislation, frameworks such as the Model AI Governance Framework (2019, refreshed 2020), the Personal Data Protection Act (PDPA), and initiatives like the AI Verify 2025 Large Language Model Starter Kit establish clear expectations: boards and executives are accountable for responsible AI adoption, oversight, and assurance. With international regulations such as the EU AI Act coming into force in 2026, scrutiny on Singaporean companies operating globally will increase.

Objective

This workshop equips executives with the knowledge and tools to lead AI governance strategically. Participants will learn to assess AI risks, define roles and responsibilities, and implement governance practices that align with both local and international standards. The focus is on enabling informed, defensible decision-making, helping organisations deploy AI safely, responsibly, and with confidence while meeting regulatory expectations.

Workshop Outline

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

What You Will Earn

Confident Oversight and Accountability: Demonstrate clear executive governance and accountability for all AI initiatives.
Strategic Risk Awareness and Mitigation: Identify, manage, and mitigate AI risks across your organisation effectively.
Practical Tools for Decision-Making: Apply actionable frameworks and checklists to guide AI adoption confidently.

Who Will Benefit

C-suite Executives: CEOs, CIOs, and CDOs driving AI strategy and governance.
AI Governance and Compliance Leads: Compliance officers, risk managers, and AI governance professionals ensuring accountability.
Board Members: Singapore-listed company boards overseeing AI deployment, risk, and strategic alignment.

Learn from the People Who Help Build AI Governance

This course is taught by specialists who work with AI governance, quality, and risk every day. They contribute to international standards, assess high-risk systems, and support organisations that need quality, reliant, and compliant AI initiatives.

Dr Martin Saerbeck

CTO and Co-Founder of AIQURIS with long experience in AI system safety, quality, and regulatory compliance. He contributes to ISO and IEC committees and has led assurance work within TÜV SÜD. His work supports sectors that rely on strict requirements for audit readiness, data quality, and accountable AI deployment.

Dr Yao Cheng

Principal AI Expert with a background in cybersecurity and trustworthy AI. She is a qualified TÜV SÜD AI Quality Trainer and an IEEE CertifAIEd Lead Assessor. She evaluates AI systems for ethical and technical criteria and participates in Singapore’s national AI standards committees.

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