Do You Trust Your AI Systems? Moving from Power BI to Trusted AI Answers | Fabcon Europe 26

Most Power BI teams already have the hardest part of a trustworthy AI foundation sitting in production and they don’t realize it. A well-built semantic model carries the measures, relationships, and business logic that make a report defensible. That’s also the raw material an agent needs before it can be trusted to answer a question at all. What has to happen between the semantic model you already built and an AI system you’d actually trust to answer and potentially act? I’ll walk through what makes a Power BI semantic model AI-ready rather than just report-ready. We’ll start with the governed Fabric foundation and One Lake as the single copy everything reasons over. How Fabric IQ fits in, turning that governed foundation into an ontology an agent can reason against instead of a schema it has to guess at. By the end you should know whether your own Fabric estate has that foundation, and what’s actually missing if it doesn’t.