NIST AI RMF Alignment Guide

Overview

NIST AI RMF is becoming the de facto standard for AI risk management in the US. Federal agencies are adopting it. Private sector organizations use it to demonstrate responsible AI practices. EU AI Act alignment discussions reference NIST AI RMF. Understanding and implementing this framework positions your organization for current and future AI governance expectations.

This workbook makes NIST AI RMF practical. Instead of a theoretical framework, you get checklists, status tracking, and implementation guidance.

What's Inside

Framework Overview
The four core functions and their purposes:

• GOVERN: Cultivate risk management culture; establish policies, processes, accountability
• MAP: Understand context; define AI system scope; identify stakeholders and impacts
• MEASURE: Assess, analyze, and track risks using quantitative and qualitative methods
• MANAGE: Prioritize and act on risks; implement controls; monitor and communicate

Current State Maturity Assessment
Self-assessment across each function:

• Initial: Ad-hoc, reactive
• Developing: Formal processes defined
• Mature: Integrated and optimized

GOVERN Function Implementation

• GV 1: Policies & Accountability
  • Legal/regulatory requirements identified
  • AI policies established and reviewed
  • Risk management processes established
  • Roles and responsibilities defined
  • Integration with enterprise risk management
  • Continuous improvement mechanisms
• GV 2: AI Literacy & Culture
  • Training provided to relevant personnel
  • Leadership commitment demonstrated
  • Risk surfacing without reprisal
• GV 3: Workforce Diversity
  • Diverse AI team perspectives
  • Affected community engagement
• GV 4: Organizational Values
  • Values integrated into AI development
  • Ethical considerations addressed

MAP Function Implementation

• Context and use case documentation
• Stakeholder identification
• Impact assessment
• Data and model documentation

MEASURE Function Implementation

• Risk assessment methodology
• Quantitative and qualitative metrics
• Bias and fairness testing
• Performance monitoring
• Drift detection

MANAGE Function Implementation

• Risk prioritization
• Control implementation
• Monitoring and review
• Communication and reporting
• Incident response

Gap Analysis & Implementation Planning

• Gap identification by subcategory
• Remediation priority assignment
• Implementation timeline development
• Resource planning

Who This Is For

• Chief AI Officers implementing AI risk management
• Risk Managers adopting NIST AI RMF
• Compliance Officers demonstrating framework alignment
• AI Governance Teams building programs
• Anyone implementing structured AI risk management

Why This Resource

NIST AI RMF documentation explains the framework but doesn't provide implementation tools. This workbook makes the framework actionable—checklists you can work through, status tracking for accountability, and gap analysis for remediation planning.

The maturity assessment helps you understand your starting point and measure progress.

FAQ

Q: Is NIST AI RMF mandatory?

A: Not for most private sector organizations, but it's becoming a best practice standard. Federal agencies have adoption requirements. Many organizations adopt it voluntarily to demonstrate responsible AI practices.

Q: How does NIST AI RMF relate to EU AI Act?

A: There's significant alignment between NIST AI RMF and EU AI Act requirements. Implementing NIST AI RMF provides a foundation for EU AI Act compliance, though additional requirements may apply.

Q: How long does implementation take?

A: Depends on your starting point and AI portfolio size. Initial assessment takes days; full implementation across a mature AI portfolio may take 6-12 months. The workbook helps you prioritize based on gaps and risk.