EU AI Act Compliance for Microsoft 365

The AI inventory gap

The EU AI Act requires organizations to know which AI systems they deploy. For most enterprises, this is the first and largest challenge, they do not have a complete AI inventory.

Microsoft 365 Copilot is visible because IT deployed it. But Copilot Studio agents were built by business teams. Power Platform AI flows were created by citizen developers. Developers adopted Cursor, GitHub Copilot, and Windsurf. Analysts use Claude and OpenAI. Specialized teams use Glean, LangDock, or Haystack. Each adoption happened in a different department, through a different procurement process, or no procurement process at all.

The EU AI Act does not distinguish between centrally deployed AI and shadow AI. Both require inventory, risk classification, and governance.

What the regulation requires

The EU AI Act creates a risk-based framework for AI governance. Key requirements for enterprises deploying AI tools:

AI system inventory. Know which AI systems are deployed, who uses them, what data they access, and what purpose they serve.

Risk classification. Categorize AI systems by risk level. High-risk systems face the strictest requirements, including conformity assessments, documentation, and human oversight.

Human oversight. Demonstrate that human oversight mechanisms are in place for AI systems that make or influence significant decisions.

Transparency. Document how AI systems work, what data they use, and what limitations they have. Users must know when they are interacting with an AI system.

Continuous compliance. The regulation requires ongoing compliance, not one-time assessments. Governance controls must be operational continuously, and evidence must be available on demand.

From gap to compliance

Rencore addresses EU AI Act compliance through the same governance framework it applies to Microsoft 365 services. Connectors to 15+ AI platforms provide automated inventory. Pre-built policies map to EU AI Act risk categories. Continuous monitoring generates the evidence regulators expect.

The compliance team gets a single dashboard showing AI governance posture across all vendors. The legal team gets exportable evidence mapped to specific regulation articles. The CIO gets a compliance roadmap that aligns with the regulation’s phased enforcement timeline.

How to start

Deploy Rencore’s AI connectors and generate your first AI inventory. This is the foundational step, you cannot classify, govern, or demonstrate compliance for AI systems you have not discovered. From inventory, extend to risk classification, policy enforcement, and evidence generation. The phased enforcement timeline means you can prioritize: prohibited practices first, general-purpose AI obligations next, full compliance evidence by August 2026.