Hi Jan,
The challenge isn't creating another semantic model, rather creating one that works across warehouses, lakehouses, BI tools, and AI applications. The challenge is that most architects don't want another multi-year migration project standing between today's architecture and tomorrow's AI initiatives.
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Our new guide, The AI-Ready Data Architecture, outlines a phased approach that builds on what already exists. Most importantly, how leveraging a semantic layer can enable you to:
- Connect and query data across sources without moving it
- Standardize business definitions for both analytics and AI
- Improve discoverability and governance across your data estate
- Enable AI agents with trusted business context
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The result is a clearer path to AI readiness without a rip-and-replace strategy.
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