Cheap to create, expensive to manage.
Added into Microsoft 365, Google Cloud, ServiceNow, Slack, data warehouses, support queues, and custom applications, enterprise AI agents have become an operating estate that the market wants to operate. So the market is now increasingly focused on the operating aspects of agents rather than the small trick of getting an agent to respond in a chat. I just read about Microsoft Agent 365, which is framed around observing, governing, and securing agents through a unified registry. Google announced Gemini Enterprise Agent Platform, build, scale, govern, and optimize. ServiceNow is talking about AI Control Tower. LangChain describes LangSmith Fleet as the management layer for ownership, authentication, auditing, sharing, and permissions.
The layer to care about is the control plane above the builder.
The builder layer is no longer enough
For the first phase of enterprise AI, the focus was business building AI agents quickly. A platform team could create a vendor intake workflow agent in minutes. A data team could create an agent that reads from a warehouse with a click of a button. A consulting team could create a research agent within an afternoon and deploy it to Slack in minutes. The focus now moves to who owns an agent, whose credentials it uses to access systems, what systems it touches, and what happens when the owner leaves, the workflow changes, the prompt drifts, the cost spikes, or the tool that the agent was built for gets deprecated.
