Governance as Cross-Cutting Function

The Principle

AI governance is not a discrete phase or checkpoint, it’s a continuous substrate that informs and is infused throughout all other risk management activities.

Why This Matters

The NIST AI RMF explicitly positions GOVERN differently from MAP, MEASURE, and MANAGE. Those three functions can be applied sequentially and iteratively. GOVERN pervades all of them simultaneously.

This architectural choice reflects a core insight: governance failures are rarely about missing a governance step. They’re about governance not being present during the technical work.

Senior leadership sets tone. Management aligns technical aspects to policies. Documentation practices enable transparency. Accountability structures define who answers for what. These elements must be active throughout the lifecycle, not bolted on at approval gates.

How to Apply

Structure governance to operate on two tracks simultaneously:

Oversight track: Policies, approval processes, compliance verification, audit mechanisms Embedded track: Team norms, documentation practices, decision-making frameworks, escalation protocols

If governance only lives on the oversight track, practitioners will route around it. If it only lives on the embedded track, it lacks organizational authority.

When This Especially Matters

Any AI system with significant potential impacts on individuals or groups. Any system where risk tolerances may evolve over time. Any organization where multiple teams contribute to AI development and deployment.

Exceptions

Very early-stage research and experimentation may operate with lighter governance structures, but the transition from experiment to deployment is precisely where governance gaps become dangerous.

Related: 05-molecule—govern-map-measure-manage-framework, 05-atom—ai-risk-measurement-challenges