NIST AI Risk Management Framework (AI RMF)
A voluntary US framework, version 1.0 published by NIST in January 2023, structured around four functions (Govern, Map, Measure, Manage), with a 2024 Generative AI Profile (AI 600-1) that identifies risk categories closely comparable to those addressed in China's and the EU's binding requirements, despite carrying no legal mandate itself.
Defined in 5 GAGE programs, which carry 7 distinct definitions of it. The wording above is taught in Certified China AI Regulatory Professional (CCARP).
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.
A voluntary framework (NIST AI 100-1, 2023) organized around four functions, Govern, Map, Measure, and Manage, that guide organizations in identifying and managing AI risk. Its Govern function calls for documented accountability structures and traceability across an AI system's lifecycle, directly relevant to the agent trail this topic builds.
A voluntary framework (NIST, 2023) organizing AI risk into four functions, Govern, Map, Measure, and Manage. Its Measure function maps to monitoring and its Manage function to incident response and recovery, making it the standards backbone under this topic. Complemented by the certifiable ISO/IEC 42001:2023 AI management-system standard.
A voluntary US framework, version 1.0 published by NIST in January 2023, structured around four functions (Govern, Map, Measure, Manage), with a 2024 Generative AI Profile (AI 600-1) that identifies risk categories closely comparable to those addressed in China's and the EU's binding requirements, despite carrying no legal mandate itself.
The US National Institute of Standards and Technology's voluntary framework (2023, with a Generative AI Profile added July 2024) built on four functions, Govern, Map, Measure, and Manage, that structure how organizations identify, assess, and respond to AI risk across the lifecycle.
A voluntary framework published by the National Institute of Standards and Technology (NIST AI RMF 1.0, January 2023, with the GenAI Profile NIST AI 600-1 added July 26, 2024) organized around four functions: Govern, Map, Measure, and Manage.
Where it is taught
The exact lessons this term appears in. The first module of every program is free with a free account.
- Risk Assessment in AI Decisions · Critical Thinking and Context Engineering, Certified AI Practitioner: Workplace Foundations
- The agent's trail: who acted, on whose authority, using what, and why, recorded for every autonomous touch of your estate · Access and the Keys, Certified AI Data Governance Professional (CADGP)
- The Liability Risk Assessment and Mitigation Strategy · Legal Frameworks and Liability Navigation, The AI Lobbyist: Certified AI Policy Strategist
- AI System Reliability and Safety Engineering · Risk, Resilience and Frontier AI, Certified AI Transformation Professional (CATP)
- Building the Audit-Ready AI Program · Lab: Regulated Industries, Certified AI Transformation Professional (CATP)
- The US Federal and State Landscape · China, EU, US: The Comparative Playbook, Certified China AI Regulatory Professional (CCARP)
- Overlapping Obligations · China, EU, US: The Comparative Playbook, Certified China AI Regulatory Professional (CCARP)
Where it shows up at work
A definition is where NIST AI Risk Management Framework (AI RMF) 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.
Reviews purpose, data, affected people, accuracy, bias, security, oversight, vendors and law for a use case, scores likelihood and impact, and documents residual risk.
2 lessons on this page teach it as a primary outcome.
Keeps the living record: each risk with a named owner, rating, treatment, residual risk, monitoring metric, threshold and review date.
2 lessons on this page teach it as a primary outcome.
Classifies AI incidents by severity, runs containment, preserves evidence, manages notification, and closes the loop with lessons learned.
2 lessons 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.
- Chief Risk Officer, AI risk editionneeds it at depth
- AI Risk Managerneeds it at depth · 2 open postings this week
- Cybersecurity Risk Analystneeds working knowledge
- AI Governance Managerneeds it at depth
- Chief Privacy Officer, AI privacy editionneeds it at depth
- AI Product Manager, responsible product editionneeds it at depth · 3 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: NIST AI RMF MAP and MEASURE; ISO/IEC 42005; EU AI Act Article 27; NIST AI RMF MANAGE.
One interview question about it
Take me through an AI risk and impact assessment you would run for a hiring tool. What do you assess, and who signs?
Asked of candidates for ai risk and impact assessment. 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.
- Privacy and data protection carries it as work you can show: A DPIA is an impact assessment; the AI version adds accuracy, bias and oversight.
- Internal audit and IT audit carries it as a claim to back up: Remediation tracking is familiar from follow-up work.
- Cybersecurity and IT carries it as work you can show: Incident playbooks and post-incident reviews are your artifacts.
Terms it appears with
Not an alphabetical neighbourhood: these are the terms taught in the same lessons, ranked by how often they appear together.