AI Governance
Is your AI governance keeping up with your AI deployment?
Most organizations, if they're honest, would say no — and IT and architecture leaders are asking each other this exact question in industry forums right now.
The cost of this problem
Fewer than a third of enterprises can reliably detect shadow AI when it's happening inside their own organization — and senior leaders use unapproved AI tools at roughly double the rate of the employees they manage, meaning the exposure usually starts above the frontline, not below it. In a regulated industry, that isn't a productivity footnote. It's sensitive data moving through tools nobody approved, compounding every week nothing changes.
Step 3 of The AI Operating Model
Govern & Sustain
We map current tool usage — approved and shadow — define who owns which agent, set approval thresholds for high-risk actions, and stand up adoption monitoring that actually gets reported to leadership on a set cadence.
Where to start
Start with the AI Governance Gap Assessment — no call required to get the initial findings. From there, governance work is scoped inside a Department or Enterprise Accelerator, or as a standalone Governance & CoE build-out.
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Ready to get ahead of your governance gap?
Book a 45-minute AI Opportunity Diagnostic. We'll map your current governance exposure and give you a prioritized remediation roadmap.
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