NIST AI Risk Management Framework (NIST AI RMF): A Detailed Compliance Guide

NIST AI RMF: An Overview

The NIST AI Risk Management Framework (NIST AI RMF) is a voluntary AI standard published by the National Institute of Standards and Technology. It was developed to help organizations identify, mitigate, and manage risks for their AI systems.

Who is in scope?

The framework applies broadly to anyone involved in the design, development, deployment, or maintenance of AI systems.

AI systems under NIST’s definition cover a wide range of solutions. They include any “engineered or machine-based system that can, for a given set of objectives, generate outputs such as predictions, recommendations, or decisions influencing real or virtual environments.” 

Even if an organization hasn’t adopted GenAI technology, they may still have systems in scope for NIST.

Why adopt the NIST AI RMF?

The NIST AI standard helps organizations ensure their AI systems are trustworthy and safe while maintaining accountability.

NIST’s high degree of flexibility and focus on AI system-level governance make it a logical place for many organizations to start building out their AI governance functions. The AI RMF contains numerous potential approaches that governance and technical teams can consider together depending on the risks and needs of an individual system.

Developers of AI systems may adopt the framework as a way to demonstrate to stakeholders or customers that they are taking steps to ensure the AI that they’ve built has been designed responsibly.

Organizations deploying AI often adopt the NIST AI RMF as a framework to ensure the AI that they are purchasing from third parties and vendors is well-managed and aligned with their internal policies.

Key requirements for compliance

1. Framing AI Risks: This involves understanding the system’s intended audience and identifying potential harms it could cause.

2. The Core Framework: The main body of the NIST AI RMF focuses on four primary functions:

1. • Govern: Focuses on establishing policies and procedures to manage AI risks effectively.
   • Map: Identifies and contextualizes AI risks within their operational environment.
   • Measure: Uses metrics and methodologies to track AI system performance over time.
   • Manage: Allocates resources to effectively handle the risks identified, ensuring proactive responses.

These functions allow organizations to comprehensively address AI risks, from design and development to long-term management and mitigation.

Non-compliance penalties

There are no legal penalties for non-compliance, as the framework is voluntary.

However, many state laws — including the Colorado AI Act — explicitly reference the NIST AI RMF as an acceptable foundation for required risk programs. That means alignment could help organizations pre-emptively meet additional regulatory requirements.

When was the AI RMF released?

NIST officially released Version 1.0 of the AI Risk Management Framework in January 2023.

The framework was developed through extensive collaboration between public and private sector experts. This multi-stakeholder effort aimed to create a practical, adaptable method to help organizations use AI responsibly while managing risks such as safety, bias, and lack of oversight.

Steps to achieve alignment with the NIST AI RMF

• • Adopt Governance Structures: Establish policies, mechanisms for accountability, and procedures to effectively oversee AI risks.
  • Identify and Map Risks: Frame AI risks in relation to their operational context. Consider how AI systems will interact with their intended users and impacted populations.
  • Measure Risks: Continuously monitor the AI system using established metrics to evaluate its performance and trustworthiness over time.
  • Manage Risks: Allocate resources to address and mitigate the impact of risks identified in the earlier steps, ensuring a comprehensive risk management approach.

Where can I learn more?