Adopting NIST AI 600-1 and the AI RMF: A Guide to Managing Generative AI Risks
What Are NIST AI 600-1 and the AI RMF?
The NIST Artificial Intelligence Risk Management Framework (AI RMF 1.0), released in January 2023, provides a voluntary, flexible, and risk-based approach to managing AI across its lifecycle. It is built on four core functions: Govern, Map, Measure, and Manage. These functions help organizations identify, assess, and mitigate risks while fostering trustworthy AI systems.
In July 2024, NIST published NIST AI 600-1, a Generative AI Profile of the AI RMF. This profile adapts the AI RMF specifically to the risks and challenges of generative AI, such as hallucinations, data leakage, copyright concerns, harmful bias, and misuse in areas like disinformation or cybersecurity. It outlines suggested actions organizations can take to manage these risks in line with the AI RMF structure.
In other words:
AI RMF = the general framework for AI risk management.
NIST AI 600-1 = the generative AI-specific companion guide that translates the RMF into concrete actions for GenAI systems.
How to Adopt the Framework in Your Organization
Adopting AI RMF and the NIST AI 600-1 profile should not be treated as an additional compliance checklist. Instead, they should be integrated into existing governance, risk, and security programs. Key steps include:
Govern (Policies & Oversight): Define organizational accountability, legal/regulatory alignment, and AI usage policies. Establish clear escalation paths for AI incidents, and set thresholds for acceptable and unacceptable risks.
Map (Risk Identification): Document AI use cases, intended purpose, stakeholders, and data sources. Explicitly map generative AI risks such as misinformation, bias, intellectual property, and model supply chain dependencies.
Measure (Risk Assessment): Test systems for hallucinations, bias, privacy leaks, and environmental impacts. Use both internal evaluations and red-teaming.
Manage (Risk Treatment): Implement safeguards like content provenance, robust incident disclosure, fallback plans for third-party dependencies, and structured decommissioning processes.
By embedding these steps into your existing appsec, risk management, or compliance functions, you can treat generative AI like other high-impact technologies, but with controls adapted to its unique risks.
Conclusion
The AI RMF provides a high-level structure for managing AI risks, and NIST AI 600-1 translates that into actionable steps for generative AI. By combining the two, organizations can create a governance program that balances innovation with responsibility, reduces exposure to legal and reputational harm, and aligns with widely recognized standards.