D&B's database of 642 million businesses was built for humans, not AI agents. So they rebuilt it.

Dun & Bradstreet reworked its Commercial Graph, a database covering 642 million businesses, because systems built for human analysts could not meet AI agents’ needs for speed, clarity, and automated decisioning. Customers using agents in credit, procurement, and supply chain workflows exposed limits in fragmented databases, ambiguous entity matching, and static relationship models.

The shift shows how enterprise data platforms must be redesigned for AI agents, not just wrapped with chat interfaces. As agents move into high-stakes workflows, vendors will face pressure to deliver real-time, structured, and context-rich data infrastructure that machines can query reliably.