Building Reusable Evidence for AI Governance Frameworks

AI governance can become complicated very quickly.

One team works with the NIST AI Risk Management Framework. Another prepares for the EU AI Act. A third is building an ISO/IEC 42001 management system. Legal, security, data and engineering may each maintain separate control lists. The result is often more governance paperwork, but not necessarily better governance.

There is a simpler way to think about it:

Build the control once. Generate the evidence once. Map that evidence to multiple requirements.

Three Frameworks, Different Purposes

NIST AI RMF, the EU AI Act and ISO/IEC 42001 are not interchangeable.

The NIST AI RMF provides a voluntary risk-management structure built around four functions:

Govern -> Map -> Measure -> Manage [1]

The EU AI Act establishes legal obligations. For high-risk AI systems, Articles 9 through 15 address areas such as risk management, data governance, technical documentation, logging, transparency, human oversight, accuracy, robustness and cybersecurity. ...

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