
Organizer, Open Data Circle
Exploring AI-native Directions for Lakehouse
AI-native workloads are redefining expectations for lakehouse systems — requiring table formats and storage layers to support richer semantics, adaptive indexing, and tighter integration with real-time and vector-driven data.
This talk examines emerging approaches for making lakehouses AI-native, with a focus on architectural shifts happening at the table-format and data-layout layers. By recognizing patterns emerging across modern open formats and storage designs, the session highlights how these developments are opening new possibilities for more adaptive, intelligent, and future-ready data platforms.

