Autonomous Data Products for the Autonomous Era: Rethinking Data Architecture for GenAI

As enterprises scale their deployment of Generative AI (Gen AI), a central constraint has come into focus: while large language models and the infrastructure  to support them are the focus of intensive investment fueling a remarkable stream of innovation, data management approaches and infrastructure depend on out-of-date assumptions that are stopping progress.

Existing platforms, optimized for human interpretation and batch-oriented analytics, are misaligned with the operational realities of autonomous agents that consume, reason over, and act upon data continuously at machine scale.

In this talk, Zhamak Dehghani — originator of the Data Mesh and a leading advocate for decentralized data architectures — presents a framework for data infrastructure designed explicitly for the AI-native era. She identifies the foundational capabilities required by Gen AI applications: embedded semantics, runtime computational policy enforcement, agent-centric, context-driven discovery.