About this session

As enterprises move toward agentic AI systems that can plan, decide, and execute autonomously, data requirements change fundamentally. It is no longer sufficient for data to be clean and available; it must be trusted, contextualized, governed, and usable by autonomous agents across workflows and domains.

This moderated discussion focuses on real-world challenges and lessons learned around preparing data for agentic AI. Participants will exchange experiences on typical blockers such as data quality and ownership, semantic consistency, real-time availability, governance and access control, and integration into existing data and AI platforms.