Microsoft Copilot promises powerful, AI-driven insights but the quality of Copilot’s output is only as good as the data behind it. Many organizations enable Copilot without first addressing the foundational data and analytics decisions that determine whether Copilot delivers value or confusion.

This session focuses on what data, analytics, and reporting teams must get right before and during Copilot adoption. Using Microsoft Fabric, Power BI, and Microsoft 365 as the reference architecture, we examine how data models, semantic layers, governance choices, and reporting practices directly influence Copilot accuracy, performance, and trust.

Attendees will learn how Copilot interacts with Power BI semantic models, how Fabric supports AI-ready analytics, and which common data mistakes undermine Copilot experiences. The session emphasizes practical guidance over hype helping teams understand what Copilot needs from their data estate and how to prepare for it realistically.

This talk is ideal for organizations planning Copilot adoption or trying to move from experimentation to meaningful, trusted AI-assisted decision-making.