AI is getting most of the attention in enterprise technology. Governance, ownership, and data quality do most of the heavy lifting behind the scenes. And yet, as organizations move from AI experiments to production deployments, trusted context is becoming a key factor in determining whether agents create business value — or operational risk.
That shift is reshaping how Salesforce, Microsoft, Snowflake, Databricks, SAP, Oracle, and others are positioning their data, governance, metadata, and integration services. The conversation is no longer just about models. It’s about whether AI systems can operate against trusted, governed, and business-relevant information.
Trusted context has become the new currency, and Salesforce has made a strategic commitment to it.
Agentic AI is exposing the problems master data management was designed to solve
Master data management (MDM) spent much of the last decade as an important but often overlooked infrastructure. AI is changing that. Agentic systems can identify duplicate records, inconsistent definitions, fragmented ownership, and poor governance the moment AI begins interacting with enterprise data and processes.
