The NIST AI Risk Management Framework provides a structured approach for managing AI risks. Whether voluntary or required for federal contracts, we help you implement Govern, Map, Measure, and Manage with clear processes and evidence.
The NIST AI Risk Management Framework (AI RMF 1.0) is a voluntary framework published by the National Institute of Standards and Technology to help organizations design, develop, deploy, and use AI systems responsibly and trustworthily.
Why this matters now: Executive Order 14110 (October 2023) made NIST AI RMF mandatory for federal agencies and increasingly expected for government contractors. It's becoming the de facto US standard for responsible AI.
Adapt to any AI system or organization
Continuous improvement throughout lifecycle
Federal agencies
Executive Order 14110 mandates NIST AI RMF adoption
Federal contractors
AI systems in government contracts must align with NIST AI RMF
Critical infrastructure
Organizations managing essential services with AI
Global enterprises
Seeking recognized AI governance standards
AI developers & providers
Building trustworthy AI products and services
Regulated industries
Financial services, healthcare, and transportation
NIST AI RMF organizes AI risk management into four interconnected functions
Establish and maintain AI risk management culture, governance structures, policies, and processes.
Identify and document AI system context, capabilities, and potential impacts.
Analyze, assess, and track identified AI risks using quantitative and qualitative methods.
Prioritize and act upon AI risks through mitigation, transfer, avoidance, or acceptance.
NIST AI RMF defines characteristics that AI systems should exhibit
AI systems perform as intended with consistent, accurate outputs.
Key considerations
AI systems do not endanger human life, health, property, or the environment.
Key considerations
AI systems maintain confidentiality, integrity, and availability.
Key considerations
Clear documentation and explanations of AI system decisions.
Key considerations
AI decisions can be understood and explained to stakeholders.
Key considerations
AI systems protect personal data and respect privacy rights.
Key considerations
AI systems treat individuals and groups equitably.
Key considerations
A practical path to NIST AI RMF adoption with clear milestones
Tailored implementations for specific contexts and use cases
Foundational framework for all organizations
Use case: General AI risk management implementation
Key components
Extended guidance for GenAI systems
Use case: LLMs, image generation, content creation
Key components
Understanding the relationship between major AI governance frameworks
| Aspect | NIST AI RMF | EU AI Act | ISO 42001 |
|---|---|---|---|
Scope | US-focused, voluntary framework | EU regulation with legal requirements | International certification standard |
Legal status | Voluntary (mandatory for US federal) | Mandatory law with penalties | Voluntary certification |
Approach | Risk-based, flexible implementation | Risk-tier classification system | Management system with controls |
Focus | Trustworthiness characteristics | Compliance obligations by role | Continuous improvement (PDCA) |
Structure | 4 functions, 19 categories | 4 risk tiers, role-based requirements | 10 clauses, Annex controls |
Certification | No formal certification | Conformity assessment required | Third-party certification available |
Timeline | 4-6 months typical implementation | Compliance by August 2025-2027 | 6-12 months to certification |
Documentation | Risk documentation, impact assessments | Technical files, conformity declarations | AIMS policies, procedures, records |
Best for | US market, federal contracts | EU market access | Global certification needs |
Pro tip: These frameworks are complementary. NIST AI RMF provides risk methodology,ISO 42001provides operational structure, andEU AI Actcompliance ensures market access.
Discuss multi-framework implementationPresident Biden's Executive Order on Safe, Secure, and Trustworthy AI (October 2023) mandates NIST AI RMF adoption across federal agencies and expects alignment from contractors.
Days for agency inventory
Days for risk assessment
Days for full compliance
Common questions about NIST AI RMF implementation
For most private organizations, NIST AI RMF is voluntary. However, Executive Order 14110 made it mandatory for federal agencies, and it's increasingly expected for federal contractors. Many regulated industries are also adopting it as a best practice standard.
While different in nature (voluntary framework vs. legal requirement), NIST AI RMF and EU AI Act share similar risk-based approaches. Organizations operating globally often implement both, using NIST AI RMF's structured approach to also satisfy EU AI Act requirements.
NIST AI RMF is a US-originated risk management framework focused on trustworthiness, while ISO 42001 is an international standard for AI management systems with certification. They complement each other—NIST AI RMF provides risk methodology, ISO 42001 provides operational structure.
A typical implementation takes 4-6 months depending on organizational size, AI system complexity, and existing governance maturity. Organizations with established risk management programs can move faster.
Yes, all four functions (Govern, Map, Measure, Manage) should be addressed, but the depth and rigor of implementation depends on your AI risk profile. The framework is flexible and allows proportionate implementation based on context.
NIST released a companion document specifically addressing risks unique to generative AI systems like LLMs. It extends the core framework with additional considerations for content provenance, hallucination risks, and human oversight requirements.
Federal agencies increasingly require contractors to demonstrate AI risk management practices aligned with NIST AI RMF. Implementing the framework positions you for contract compliance and demonstrates responsible AI governance to government clients.
Yes, VerifyWise maps its governance controls to NIST AI RMF requirements. Our platform helps you document your AI systems, conduct risk assessments aligned with the four functions, and generate evidence for audits and compliance reviews.
Start your risk management journey with our guided assessment and implementation tools.