AI Governance Microsoft 365: Proven Framework for 2026 Success

Last year I sat in a governance review with a mid-sized professional services firm in Madrid. They had deployed Microsoft 365 Copilot to 800 users six months earlier. Usage was high, productivity gains were measurable — and then legal came back with a question: "Can you tell us exactly what data Copilot accessed during that contract negotiation in March?" The answer, at that point, was essentially no. No audit trail configured. No sensitivity labels on the relevant documents. No DLP policies covering Copilot interaction channels. That conversation is more common than it should be. Organizations move fast to capture the productivity value of AI — which is the right instinct — but the governance layer lags by months. The problem is that closing that gap reactively, after an incident or an audit, costs far more in remediation than doing it right from the start. My recommendation is direct: governance is not a phase 2 activity. You build it in parallel with your Copilot rollout, not after. Here's the framework I use with customers. Before you start These prerequisites are non-negotiable before you configure any AI governance controls in your M365 tenant: !Before you start — AI Governance Fundamentals: A Practical Framework for Enterprise Microsoft 365 [ ] Microsoft Purview AI Hub enabled in your tenant — without this, you have no baseline visibility into existing AI activity; it costs nothing to enable and takes minutes [ ] Audit logging status confirmed — verify that Microsoft P