AI has dramatically reduced the time required to turn an idea into a working application. Across insurance organizations, local teams are building dashboards, assistants, and workflow tools that deliver real value. Yet many of these successes struggle when their data and outputs must cross teams, regions, and systems.
A local application often works because the people around it share an understanding of definitions, trusted sources, exceptions, and business judgment. At enterprise scale, that context is no longer guaranteed. Differences in data grain, classifications, ownership, and terminology begin producing conflicting answers.
This session will examine the common reasons successful AI POCs stall at enterprise boundaries and introduce a federated knowledge-layer concept that allows business context to be shared without forcing every team into one centrally built application.
Attendees will learn:
- Why a useful local POC is not yet a repeatable enterprise capability
- Where context breaks as applications cross organizational boundaries
- How shared definitions, relationships, and accountability can support enterprise scale while preserving local speed