AI GUIDE FOR BOARDS IN SINGAPORE
Section III: Governance and Oversight
6.1 Singapore’s AI Governance Approach
Singapore's Approach to AI Governance focuses on developing a trusted ecosystem through the provision of guardrails to manage risks while enabling space for innovation. Rather than enacting a singular, overarching AI law, Singapore takes a pragmatic approach by tapping on existing regulations and focusing on outcomes.
systemic AI risks when embedded into models and automated decisions.
Organisations should therefore maintain: • Clear data ownership. • Auditable lineage and retention practices. • Appropriate access controls. • Robust consent management. • Disciplined data lifecycle governance. In Singapore, these obligations are underpinned by the Personal Data Protection Act and overseen by the Personal Data Protection Commission.
6.1.1 e foundational data layer
AI systems depend heavily on enterprise data. As a result, AI governance and data governance are closely connected. Boards should recognise that poor data quality, ambiguous data lineage, unclear consent management, or fragmented governance can rapidly compound into
Boards should ensure the management treats data governance as a strategic capability rather than solely as a compliance exercise.
Singapore’s Approach to AI Governance
Data and privacy foundation
Sectoral mandates
Practical AI trust tools
Statutory compliance via the Personal Data Protection Act
For example, the Monetary Authority of Singapore FEAT principles
Tools such as the AI Verify Testing Framework
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