The architecture decisions defining enterprise AI

From Databricks leaders and their customers

There is more AI activity than AI value. Most enterprises have the deployments, the budgets and the ambition. And yet they still cannot point to the outcomes. The gap is not talent or models. It’s that yesterday's data and application architectures were never built for systems that reason, decide and act.

The leaders pulling ahead have stopped asking what AI can do. They’re asking what decisions and workflows AI should own. Then they rebuild the foundation to make that possible.

Inside, Databricks executives and their customers share the architectural and operational shifts separating organizations that scale from those that stall, the role of governance and semantic layers in trusted, agentic systems, and five strategic plays for the next 18 months.

Download the eBook to see what teams building this architecture know.

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