For leadership and senior management
AI risk management for leadership
You run the framework the board approves.
Under the MAS AI Risk Management Guidelines (AIRG), senior management turns the board's direction into a working system. You implement the AI risk management framework across the firm, institute controls across the AI lifecycle, set clear roles and responsibilities across business and control functions, escalate material AI risks and incidents to the board in good time, and make sure the firm has the competence and resources to manage AI well. The board owns the appetite; you own whether the firm actually operates within it.
The practical test is whether the framework holds when it is used: that AI is identified and rated consistently, that controls match the materiality, and that a problem surfaces and escalates rather than sitting unseen. The fuller, step-by-step guide for the Board and Senior Management is the executive guide to adopting generative and agentic AI.
Where to start
- The executive guide to adopting generative and agentic AI - the fuller step-by-step guide for the Board and Senior Management.
- The complete guide to AI risk management in finance in Singapore - the whole picture in one place.
- The AIRG explained - the guidelines your firm is supervised against.
- The AIRG in practice - identification, inventory, materiality and lifecycle controls as a working system.
- Governing AI at scale - keeping control as the number of AI systems grows.
- The board above and the three lines below: boards, business lines (first line), risk and compliance (second line), and internal audit (third line).
I developed the AIRG while leading AI risk supervision at MAS, and now advise senior management independently. I am publishing more on AI risk management; subscribe to get it, and future updates on the AIRG.