AI GUIDE FOR BOARDS IN SINGAPORE
Section III: Governance and Oversight
7.4.2 Clarifying executive accountability
7.4.3 Strengthening board-management engagement
Management accountability for AI should be clearly assigned to a named executive leader.
e pace of AI development may outstrip traditional annual or quarterly governance cycles. Boards should consider more agile engagement models when quarterly board cadence may not su ce. Examples include: • Regular check-in sessions between relevant board committees and the executive responsible for AI. • Joint brie ngs across risk, audit and technology committees. • Focused deep dives into high-risk AI deployments. • Periodic external brie ngs on regulatory and market developments. If accountability for AI failure is unclear before an incident occurs, accountability a er the incident is likely to be even more unclear.
Depending on organisational scale and maturity, this may include: • A dedicated Chief AI O cer. • A Chief Data and AI O cer. • Another appropriately empowered senior management executive. is individual should possess su cient authority to coordinate across technology, legal, risk, operations, compliance and business functions. Where AI transformation is a strategic priority, boards may also require direct CEO accountability for enterprise AI outcomes.
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