Iโve been thinking about how enterprise AI is changing, especially after attending the Data + AI Summit 2026 and hearing Ali Ghodsi emphasize the importance of enterprise context. It made the direction much clearer to me. We already have very capable AI models. The bigger challenge now is giving those models the right understanding of the business.
What does this data mean?
Which metric should the AI trust?
Who can access it?
What business rules should it follow?
And what action should it take next?
That also made me think more about the 4Cs: Context, Control, Choice, and Cost. Context helps AI understand the business. Control helps enterprises govern what AI can access and do. Choice gives organizations flexibility across models and tools instead of locking everything into one path. Cost becomes critical when AI moves from a few experiments to thousands or even millions of agent actions.
This is why I find the direction Databricks is taking with Genie, Genie Ontology, Unity Catalog, and agents very interesting. We spent years building platforms that make enterprise data usable for people. Now we are entering a phase where that same data, meaning, governance, and business knowledge need to become usable by AI agents.
For me, the 4Cs are becoming a simple way to think about enterprise AI: give AI the right Context, keep the right Control, preserve Choice, and understand the Cost.
Would love to hear how others in the Databricks Community are thinking about this.
