AI is only as good as the data model behind it.
In Microsoft Fabric, the semantic model is no longer just the layer that powers reports. It has become the foundation for Data Agents, shaping how AI understands data, answers questions, and delivers business value.
The challenge? AI requires consistency, context, and trust. Without a standardized semantic layer, agents can produce different answers, misunderstand business definitions, and become difficult to scale.
In this session, you'll discover why well-structured semantic models are essential for trustworthy AI. We'll demonstrate how generated semantic models provide the metadata, governance, and consistency that Data Agents need to deliver reliable insights at scale.
You'll also see how Fabric IQ adds business context and intent, helping agents move beyond simply answering questions to delivering meaningful business outcomes.

Key takeaways
Why semantic models are the foundation of trustworthy AI in Fabric
How metadata and standardization improve agent quality and reliability
Why context is critical for delivering valuable AI-driven insights
How organizations can scale AI-enabled analytics with confidence
Audience
Data professionals, BI developers, analytics engineers, and Fabric practitioners interested in AI and semantic modeling.

Prerequisites
Basic knowledge of Fabric semantic models and analytics concepts.