Practical guidance on Microsoft Copilot, Copilot Studio, Power Platform, Azure AI, governance and security.
Before enabling Copilot, review data access, sensitivity labels, licensing and user readiness. These five checks reduce oversharing risk and speed up value.
Read article: Five readiness checks before you roll out Microsoft Copilot →Start with a narrow, high-value use case, ground the agent in trusted knowledge, define escalation paths and test with real users before wider release.
Read article: Designing your first Copilot Studio agent: a practical checklist →A CoE provides guardrails, reusable components and support so citizen developers can innovate without creating shadow IT.
Read article: Why a Power Platform Centre of Excellence pays for itself →Production generative AI needs evaluation, grounding with AI Search, content safety, monitoring and cost controls, not just a good prompt.
Read article: From proof of concept to production with Azure OpenAI →Effective governance is clear, proportionate and embedded in the operating model, covering ownership, acceptable use, risk review and measurement.
Read article: Building an AI governance framework that people will follow →Sensitivity labels, least-privilege access, data loss prevention and ongoing access reviews are the foundations of secure Copilot use.
Read article: Protecting sensitive data in a Copilot-enabled organisation →Speak with a Microsoft AI specialist about your Copilot, Azure and governance priorities.