The Single Source of Truth: Building Data Foundations for Agentic AI
Traditional data management was built to give humans consistent, trustworthy records to work from. Agentic AI demands something more dynamic: data that agents can query, reason over, and act on continuously, without waiting for a human to interpret it first. That shift changes what "good" data actually looks like.
This webinar explores how data foundations must evolve to support agentic AI—moving from static, periodically-updated records toward connected, real-time, machine-consumable data. We'll cover what it takes to make data not just accurate, but usable by autonomous systems making decisions at machine speed.
Key Takeaways:
1️⃣ Rethinking "Good" Data: How agentic AI changes the requirements for data quality and structure.
2️⃣ Real-Time Unification: Why static, periodic data processes fall short for continuously acting agents.
3️⃣ Machine-Readable Trust: Designing authoritative records that agents can reliably reason over.
4️⃣ Data Stewardship for Autonomy: How data ownership roles must adapt as agents become primary data consumers.