What Is AI Governance?

AI governance is the set of controls, policies, and accountability structures that let a company use artificial intelligence safely and defensibly: deciding which models and data are permitted, who approves use cases, how outputs are reviewed, and how risk is monitored. In a private equity context it protects enterprise value: a portfolio deploying AI without governance carries unpriced risk.

How it works in practice

Governance is an operating layer, not a policy document. It defines approved models and data boundaries, an approval path for new use cases, review standards for AI-generated output, and monitoring that a CISO or board can rely on. The Enterprise AI Control Plane is the framework for building that layer once across a portfolio: one standard, applied consistently, rather than each portco improvising its own.

Where firms get it wrong

The two failure modes are opposite. One is a blanket ban that pushes AI use into the shadows, where it happens anyway without controls. The other is unmanaged adoption: teams wiring models to sensitive data with no approval, review, or record. Both leave the same result at exit: a buyer's diligence finding an AI footprint no one can account for.

When you need it

A portfolio already using AI in production, a thesis that expands AI use, or a security and trust posture that has to survive a buyer's diligence all make governance load-bearing. That work runs through the Improve engagement.