Executive Comparison of AI Governance Frameworks for Risk & Compliance

Artificial Intelligence (AI) is becoming integral to enterprise operations and risk management, including emerging Autonomous IRM (Integrated Risk Management) initiatives where AI agents autonomously assist in identifying and managing risks. Executives and boards need to ensure such AI deployments are trustworthy, compliant, and aligned with business objectives. Several frameworks have emerged to govern AI risk and compliance. Below is a comparison of three key frameworks – ISO/IEC 42001 (the new AI Management System standard), the EU AI Act (forthcoming European regulation), and the NIST AI Risk Management Framework (RMF) (a U.S. voluntary guideline) – focusing on what executives should understand, monitor, and prioritize in each.

Samantha "Sam" Jones

Samantha “Sam” Jones is the lead research analyst for the IRM Navigator™ series and a core contributor to The RiskTech Journal and The RTJ Bridge. As a digital editorial analyst, she specializes in interpreting vendor strategy, market evolution, and the convergence of technology with enterprise risk practices.

As part of Wheelhouse’s AI-enhanced advisory team, Sam applies advanced analytical tooling and editorial synthesis to help decode the structural changes shaping the risk management landscape.

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