The battle for enterprise AI is being fought on two fronts. Data platforms like Snowflake build agents from a governed data foundation (Data+AI), while model companies like OpenAI push general agents down into enterprise systems (AI+Data). The winner controls the core workflow.
The competition between data platforms and model companies is not about providing a better tool. It is a battle to define the future enterprise operating model, where core processes are executed by a collaboration of humans and AI agents, fundamentally changing roles and workflows.
As AI moves from answering questions to executing actions, governance becomes paramount. Previously a backend IT concern, robust governance for permissions, auditing, and accountability is now an essential prerequisite for deploying production-ready AI agents safely.
The most valuable position in the future enterprise AI stack is not the chat interface. It is the control layer that orchestrates task distribution—receiving user intent, accessing context, and deciding which systems and agents are authorized to execute actions.