MAS AI Risk Management Guidelines (AIRG)
The Monetary Authority of Singapore's Consultation Paper P017-2025 (13 November 2025; consultation closed 31 January 2026; final guidelines not issued as of 15 August 2026), proposing four sections: oversight; key AI risk management systems (AI identification, inventory, materiality assessment); key AI life cycle controls; and capabilities and capacity. Taught throughout as proposed supervisory expectations, never in-force rules. (see Topic 6.8)
Defined in 3 GAGE programs, which carry 4 distinct definitions of it. The wording above is taught in Certified AI Governance Professional (CAIGP).
How each discipline defines it
The same term does different work depending on who is using it. These are the definitions as each program teaches them, unedited.
The Monetary Authority of Singapore's proposed guidelines on AI risk management for financial institutions, released for consultation 13 November 2025, with the consultation closed 31 January 2026 and final guidelines not yet issued as of 15 August 2026; a separate, sector-specific, still-proposed instrument distinct from the PDPC's finalised, general-application generative AI guidance, used in this topic only to illustrate the instrument-maturity ladder, not as this topic's own subject matter.
The Monetary Authority of Singapore's Consultation Paper P017-2025 (13 November 2025; consultation closed 31 January 2026; final guidelines not issued as of 15 August 2026), proposing four sections: oversight; key AI risk management systems (AI identification, inventory, materiality assessment); key AI life cycle controls; and capabilities and capacity. Taught throughout as proposed supervisory expectations, never in-force rules. (see Topic 6.8)
Singapore's Monetary Authority's proposed guidelines, launched for consultation in November 2025, confirmed via a written parliamentary reply for the 5 August 2026 sitting to apply to all AI use cases by financial institutions, including agentic AI. As of that date, still proposed and "to be finalised soon," not yet a finalized, binding text. Sector specific (financial institutions) and jurisdiction specific (Singapore). (see Topic 10.2)
MAS's proposed AI risk management guidelines, consultation opened 13 November 2025, closed 31 January 2026, confirmed by a 5 August 2026 parliamentary reply to apply to all AI use cases by financial institutions including agentic AI, and still described in that reply as guidelines that will be finalised soon. Classified GUIDANCE, EMERGING, as of 16 August 2026. Full depth (see Topic 10.2).
Where it is taught
The exact lessons this term appears in. The first module of every program is free with a free account.
- The Instrument Landscape · The Agent, Deconstructed, Certified Agentic AI Governance Professional (CAAGP)
- The Binding Spine · The Law and the Regulators, Certified Agentic AI Governance Professional (CAAGP)
- PDPA for AI: What Singapore Actually Allows · Consent, Purpose, and the Law of Data, Certified AI Data Governance Professional (CADGP)
- The one-document lab: one AI system, three regimes, zero duplicate work · The World's Rulebooks, Certified AI Governance Professional (CAIGP)
Where it shows up at work
A definition is where MAS AI Risk Management Guidelines (AIRG) starts. The lessons above teach it inside the competencies below, which are what job descriptions ask for and what the GAGE credential records. Every link here is drawn from the same careers map that builds a role's readiness check.
Compares the EU AI Act, NIST AI RMF, ISO/IEC 42001 and sector rules by intent and control objective, and says where they do not overlap.
2 lessons on this page teach it as a primary outcome.
Applies IMDA's Model AI Governance Framework, AI Verify and the PDPA alongside Western frameworks for organizations operating across Asia.
2 lessons on this page teach it as a primary outcome.
Collects, labels and preserves the evidence that a control operated, a decision was made, and a claim can be defended to an auditor or regulator.
One lesson on this page teach it as a primary outcome.
Roles that hire for it
Each role page shows the full competency set, what the seat decides, and a readiness check against your own evidence.
- Senior AI Compliance Analystneeds it at depth
- Security Compliance Managerneeds it at depth · 4 open postings this week
- AI Compliance Managerneeds it at depth · 2 open postings this week
- AI Compliance Specialistneeds working knowledge · 1 open posting this week
- AI Controls Analystneeds working knowledge
- Compliance Analystneeds working knowledge · 2 open postings this week
How job descriptions say it
Postings rarely use the textbook word. These are the phrases the careers map reads as asking for the competencies above.
Where the frameworks place it: EU AI Act; NIST AI RMF; ISO/IEC 42001; IMDA Model AI Governance Framework.
One interview question about it
Map one control to the EU AI Act, NIST AI RMF and ISO/IEC 42001 at once, and tell me where the mapping breaks.
Asked of candidates for framework crosswalking without false equivalence. Answering it in your own words is exactly how a GAGE topic is passed, and the credential records the pass where an employer can check it.
If you come from another field
Some backgrounds already carry this competency, and the readiness check gives credit for it.
- Compliance and regulatory affairs carries it as work you can show: Audit-ready documentation is what you produce.
- Internal audit and IT audit carries it as work you can show: Evidence evaluation is the profession.
- Project and program management carries it as a claim to back up: Decision logs and repositories are familiar.
Terms it appears with
Not an alphabetical neighbourhood: these are the terms taught in the same lessons, ranked by how often they appear together.