The NIST AI Risk Management Framework (AI RMF) provides a voluntary, flexible framework for managing AI risks. While not legally binding, it's becoming the de facto standard for AI risk management in the US and beyond.

Framework Structure

The AI RMF has two main components:

Part 1 — Foundational Information:

• Defines AI risk concepts and characteristics of trustworthy AI
• Seven characteristics: valid & reliable, safe, secure & resilient, accountable & transparent, explainable & interpretable, privacy-enhanced, fair with harmful bias managed

Part 2 — Core Functions

GOVERN: Establish AI governance structures

• Define roles and responsibilities for AI oversight
• Create organizational policies for AI development and deployment
• Foster a culture of responsible AI
• Engage diverse stakeholders in governance decisions

MAP: Identify and contextualize AI risks

• Understand the AI system's context of use
• Identify potential benefits and harms
• Map stakeholders and affected communities
• Document assumptions and limitations

MEASURE: Assess and analyze AI risks

• Develop metrics for trustworthiness characteristics
• Test for bias, accuracy, robustness, and security
• Track risks over time with monitoring
• Use both quantitative metrics and qualitative assessments

MANAGE: Prioritize and act on AI risks

• Prioritize risks based on severity and likelihood
• Implement risk mitigation strategies
• Establish incident response procedures
• Communicate risks to stakeholders

Practical Implementation

Start with these steps:

1. AI inventory: Catalog all AI systems in your organization with their risk profiles
2. Risk assessment: For each system, assess potential harms across all seven trustworthiness characteristics
3. Controls mapping: Map existing controls to identified risks; identify gaps
4. Monitoring plan: Define metrics and review cadences for ongoing risk tracking
5. Incident response: Create procedures for AI-related incidents

NIST AI RMF vs. EU AI Act

Many organizations use NIST AI RMF as the implementation framework for EU AI Act compliance.