Every enterprise AI initiative that stalls at scale traces back to the same root cause: the foundation was never architected for it. The architecture underneath : data, governance, process context, and the operating model that connects them.

This deep dive pre-conference session brings together Enterprise Architects and program leaders for an intensive deep dive into what "AI-enabled" requires at the architectural level. 
We move beyond vision statements and into the structural decisions that determine whether AI compounds value or compounds risk.

The session is built around SAP's Context System, five layers of enterprise context that agents need to reason correctly (data, semantic, process, governance, and intent) and the architectural foundations that must be in place before any of them work at scale: Clean Core readiness, data architecture with SAP Business Data Cloud, the SAP Business AI Platform as the build-and-govern layer, and the agent lifecycle governance model through SAP AI Agent Hub. This is a working session. Expect architectural patterns, decision frameworks, real customer examples, and direct interaction with SAP's architecture leadership. You will leave with a clear assessment of where your organization stands and what to priorities next.

Key Takeaways:

• Understand organization's AI-readiness across all five context layers — not just data, but semantic, process, governance, and intent
• Understand the architectural pre-requisites that separate organizations scaling AI from those stuck in pilots
• Work through decision frameworks for Clean Core prioritization, data architecture design, and agent governance models
• Learn from customer examples: what high-performing organizations did differently in their first 12 months