Operationalizing model inventories, evaluation cadence, audit logs, and human-in-the-loop checkpoints to satisfy the EU AI Act, NIST AI RMF, ISO/IEC 42001, and
An enterprise AI governance program operationalizes control over the whole AI estate: inventorying every system (built and bought), risk-classifying against frameworks like the EU AI Act, enforcing lifecycle gates (documentation, testing, monitoring), and running incident and audit machinery. In 2026 it's a funded operating function: the license to deploy at scale in any regulated context.
The twin failure modes are theater (policies nobody operationalizes) and throttle (review boards that strangle delivery). Programs that work are proportionate and embedded: controls built into platforms and pipelines, risk-tiered lanes, and governance staff who measure their own cycle times like a product team.
With the inventory: you can't govern what you can't see, and most enterprises find 2–5x more AI in use than expected, especially vendor-embedded. Inventory plus risk-tiering unlocks everything else.
Proportionality and self-service: fast lanes for low-risk uses, controls baked into approved platforms, published review SLAs. Measure governance throughput: a board that can't keep pace is a design failure.