AI in Power BI is only as good as the data and metadata behind it - and most semantic models are nowhere near ready.

Poor schemas, vague column names, missing descriptions, and unchecked relationships confuse AI copilots, produce inconsistent answers in Q&A, and erode user trust. This session focuses on the unglamorous, but critical work required to make AI actually useful in Power BI.

You’ll learn at the session:
- How to make semantic models AI-ready,
- Optimize data schemas for clarity and simplicity,
- Review and refine tables & column metadata,
- Apply linguistic modeling for business meaning,
- Define AI instructions,

By the end of the session, you’ll know exactly when a model is “AI-ready”, how to mark it as such, and how to safely let users test and trust AI-driven insights.

This session is ideal for Power BI professionals, analytics engineers, and data teams who want AI features to deliver real value.