Confluent CTO: AI agents expose a data timing gap

Confluent CTO Stephen Deasy highlights a critical timing gap between AI agents that require continuous real-time data and enterprise data systems that refresh in batches, stressing the need to adapt data architectures for real-time, governed AI workflows. He advocates closer governance at the data source, decoupling data from models for faster experimentation, and evolving lakehouses towards more real-time data integration under governance.

This Wire brief sits within Fusion42's coverage of AI Agents and Data Infrastructure.