AI Governance

Stand up an AI program that satisfies regulators while enabling teams to ship responsibly.

Definition

What is AI Governance?

AI Governance is the framework of policies, roles, controls and review gates that ensures artificial-intelligence systems are developed and operated safely, lawfully and in line with organizational values. It spans data sourcing, model development, deployment, monitoring and retirement.

Overview

How we approach it

We translate frameworks such as the NIST AI RMF, EU AI Act and ISO/IEC 42001 into operational controls your teams can actually follow.

We build a model inventory and risk-tier every use case so high-impact systems get more scrutiny than low-impact ones.

Use-case intake, model review boards and post-deployment monitoring close the loop.

What we do

Scope of the engagement

Policy & framework design

Responsible-AI principles, acceptable use, prohibited use, third-party AI procurement.

Model inventory & tiering

Central registry with risk tier, owner, data lineage and review status.

Review boards & intake

Lightweight intake forms, tiered review gates and exec-level escalation paths.

Regulatory readiness

EU AI Act gap analysis, NIST AI RMF mapping, ISO 42001 management-system buildout.

Outcomes

What you walk away with

Defensible AI program that satisfies regulators and customers
Shorter time-to-deploy for low-risk AI use cases
Reduced exposure to reputational and legal risk

FAQ

Common questions

Does this slow down our AI teams?

Tiered review means low-risk projects move faster, not slower. Only high-impact systems trigger deep review.

EU AI Act — do we need to comply?

If you operate in the EU or serve EU users, yes. We can map your exposure in 2 weeks.

Other services

Ready to scope a ai governance engagement?

Talk to an advisor