Overview & purpose

ISO/IEC 42001 defines how to build and operate an AI Management System (AIMS), while the NIST AI Risk Management Framework (RMF) focuses on how to identify, measure, and mitigate AI risks. Interoperability enables organisations to leverage a single set of controls that serve both frameworks simultaneously — providing consistent governance and regulatory readiness.

Interoperability principles

• Equivalence: Each RMF function maps to one or more ISO clauses with similar intent.
• Evidence reuse: Same records serve both management system and risk function verification.
• Continuous improvement: ISO §10 and RMF “Manage” share a common feedback loop.
• Traceability: Every metric, risk, or control is linked to an auditable source document.

Control mapping table

Unified governance model

• Top-level Policy Layer: Master AI Policy, Ethical Charter, Risk Appetite Statement.
• Operational Layer: Risk Profiles, Incident Logs, Training Records, Supplier Assessments.
• Evidence Layer: Dashboards, Audits, PMM Reports, CAPA Trackers.
• Each layer mapped 1:1 to RMF functions and ISO sections for traceability.

Evidence reuse & audit alignment

• Single evidence register tagged with dual framework IDs (e.g., EV-42001-NIST-15).
• Audit trail links each metric or record to both ISO and NIST requirements.
• Automated cross-referencing saves time during external audits and self-assessments.
• Regulatory submissions (CE Marking / AI Act Annex IV) reuse ISO 42001 evidence set.

Integration architecture

AIMS Policy Repository → Risk Register (API) → NIST RMF Dashboard ↔ Trustworthiness Metrics Engine  
  ↳ Evidence Database (shared keys + dual framework tags)  
  ↳ CAPA System → Audit Reports → Management Review Outputs

Common pitfalls & solutions

• Duplicate records: Maintain a single evidence source of truth for both frameworks.
• Terminology confusion: Use a cross-reference glossary (Govern ↔ Leadership, Measure ↔ Performance).
• Audit fragmentation: Plan integrated audit program covering both RMF & ISO controls simultaneously.
• Over-documentation: Automate data feeds from dashboards and risk registers.

Operational benefits

• Unified framework reduces governance overlap and increases transparency.
• Evidence reuse accelerates ISO certification and NIST compliance assessments.
• Integrated reporting enables one-click Governance Board review packs.
• Common taxonomy simplifies training and system design for AI teams.

Implementation checklist

• Mapping table approved by Compliance Lead & AI Governance Board.
• Evidence register updated with dual framework tags.
• Unified audit schedule created for ISO & NIST assessments.
• Cross-training completed for risk & audit teams.
• Integration dashboards reviewed quarterly for consistency.

© Zen AI Governance UK Ltd • Regulatory Knowledge • v1 13 Nov 2025 • This page is general guidance, not legal advice.