Expertise / AI governance
Adopt AI responsibly, and be able to prove it.
We help you govern artificial intelligence (AI) the way you govern the rest of the program: clear ownership, managed risk, and controls that scale as adoption grows.
Why AI governance now.
AI adoption is outpacing the governance around it. The goal isn’t to slow the business; it’s to enable responsible use with ownership, risk management, and evidence of how decisions get made, so AI use holds up to scrutiny.
What AI governance covers.
Coverage spans operating model, risk, and controls.
AI governance operating model.
AI risk management.
Policy and acceptable use.
Controls and evidence mapped into the common control framework.
Alignment to emerging frameworks and regulation, including ISO/IEC 42001 and the NIST AI Risk Management Framework.
Evidence of AI oversight.
Governed AI adoption lets the business move faster because the guardrails are already there.
Teams know which AI uses are approved, which need review, and who to ask.
AI risk is assessed with the same rigor as other program risk, not case by case.
There is a record of how AI decisions were made when a customer or regulator asks.
Controls extend to new tools as adoption grows, without starting governance over.
How we operationalize it.
AI governance runs through the four service lines and one method (Assess, Design, Implement, Operate, Improve), so it evolves with the technology and the rules. It is built in Build and Implement and kept current in Managed GRC.
Start with the program, not the framework.
Talk with a senior advisor about the decisions, ownership, and operating capability your organization needs next.
A conversation with a senior practitioner, not a sales gatekeeper.