Microsoft ships new AI capabilities in Power Platform almost every month. AI Builder, Copilot in Power Apps, Copilot in Power Automate, Copilot in Dynamics 365 — the pace is relentless.
For IT leaders and platform administrators, the challenge isn't keeping up with features. It's answering a harder question: who decides what gets turned on, and how do we know it's being used responsibly?
The default is "on"
Many Copilot features are enabled by default at the tenant level. If you haven't explicitly configured policies, your users may already be interacting with AI in ways you haven't anticipated.
This isn't inherently bad. But it does mean that the window for proactive governance is shorter than most organizations realize.
What governance actually looks like
AI governance isn't a document that lives in SharePoint. It's a set of operational decisions:
Who can build with AI?
Not every maker needs access to AI Builder or custom Copilot prompts. Define which environments allow AI components, and which roles can create them.
What data can AI access?
DLP policies need to account for AI-specific data flows. A custom connector that sends Dataverse data to an external AI model is a data loss prevention concern — even if the connector itself seems harmless.
How do you monitor usage?
You can't govern what you can't see. Establish visibility into:
- Which users are interacting with Copilot
- What prompts are being sent to AI Builder
- Where AI-generated content is being used in production flows
What happens when AI gets it wrong?
Copilot will produce incorrect outputs. AI Builder models will make wrong predictions. The question is whether you have a process for catching, reporting, and correcting these errors — or whether they silently propagate through your business processes.
The compliance dimension
For regulated industries, AI governance isn't optional. GDPR, HIPAA, SOC 2, and industry-specific frameworks all have implications for how AI processes and surfaces data.
Key questions for compliance:
- Can you demonstrate what data AI has access to?
- Can you produce an audit trail of AI-generated decisions?
- Do your data processing agreements cover AI workloads?
- Are you retaining AI interaction logs in compliance with your retention policies?
Start simple
You don't need a 50-page AI governance framework. You need answers to three questions:
- What's enabled? — Audit your tenant for AI features that are currently active
- Who's using it? — Get visibility into AI adoption across your environments
- What are the rules? — Define acceptable use policies that are specific enough to be actionable
Governance enables adoption
This is the part that gets lost in the conversation. Good governance doesn't slow down AI adoption — it accelerates it.
When leadership, compliance, and security teams trust that AI is being governed responsibly, they're far more likely to approve broader rollout. The organizations that move fastest with AI are the ones that invested in governance first.
Building an AI governance framework for your Power Platform environment? Let's talk.