NIST AI Risk Management Framework (AI RMF 1.0)
Framework reference — controls, obligations, and mapping to US state AI laws.
Last verified April 30, 2026
Overview
The NIST Artificial Intelligence Risk Management Framework (AI RMF 1.0) is a voluntary framework released by the U.S. National Institute of Standards and Technology on January 26, 2023, intended to help organizations design, develop, deploy, and use AI systems in a manner that manages risks to individuals, organizations, and society.
The framework is built around four core functions:
- GOVERN — establish a culture of risk management with policies, processes, accountability structures, and oversight
- MAP — identify the context, intended uses, stakeholders, and risks of an AI system
- MEASURE — assess, analyze, and track AI risks and impacts using qualitative and quantitative methods
- MANAGE — allocate risk resources and treat identified risks based on assessed impact
NIST also released the Generative AI Profile (NIST AI 600-1) in July 2024, which provides specific guidance for the unique risks of generative AI systems, including confabulation, harmful biases, intellectual property issues, and value chain risks.
The framework PDF is paired with the NIST AI RMF Playbook, an interactive companion resource hosted on the NIST AI Resource Center (AIRC) that supplies *suggested actions*, transparency-and-documentation prompts, and references for each subcategory across all four functions. The Playbook is not distributed as a PDF — it is maintained as a living web resource and is updated independently of the framework PDF itself.
While the RMF itself is non-binding, it is widely referenced in U.S. state AI laws, federal procurement requirements, and emerging international AI policy. It is not directly certifiable — there is no "NIST AI RMF certification" issued by NIST itself. ISO/IEC 42001 provides a complementary certifiable management-system standard for organizations that need an accredited certificate.
Governance operating model
For teams turning the GOVERN function into decision rights, committees, lifecycle gates, and escalation paths, pair this framework reference with the AI governance guide.
Core controls & obligations
Specific controls and obligations from NIST AI RMF, with section references where available.
- GovernanceRole: bothGOVERN 1-6
GOVERN function: establish policies, processes, structures, and accountability for AI risk management across the organization, including senior leadership oversight and a risk-based culture.
- Risk assessmentRole: bothMAP 1-5
MAP function: identify the context, intended uses, stakeholders, and risks of each AI system, including categorization of impacts on individuals, communities, and the organization.
- Risk assessmentRole: bothMEASURE 1-4
MEASURE function: assess, analyze, and monitor AI risks using both quantitative and qualitative methods, including bias evaluation, robustness testing, and explainability assessments.
- GovernanceRole: bothMANAGE 1-4
MANAGE function: prioritize and treat identified risks, allocate resources, and implement risk response strategies including mitigation, transfer, acceptance, or avoidance.
Mapped to US state laws
Common controls in NIST AI RMF that satisfy or overlap with US state AI law obligations. Mapping strength indicates how closely the framework control corresponds to the statutory requirement.
- Transparency in Frontier Artificial Intelligence Act (TFAIA)strong mapping
- California AI Transparency Actweak mapping
- Colorado Artificial Intelligence Actstrong mapping
- Illinois HB 3773 (AI in Employment Decisions)partial mapping
- NYC Local Law 144 (Automated Employment Decision Tools)partial mapping
- Texas Responsible Artificial Intelligence Governance Act (TRAIGA)partial mapping
Sources
Last verified April 30, 2026
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