Most enterprise AI tools pitch themselves to business analysts and non-technical managers, promising agent-building with no code required. Google went the other direction.
The company's new Gemini Enterprise Agent Platform is aimed squarely at IT departments and developers. Rather than putting agent-building — where AI handles automated tasks like pulling data, summarizing reports, or triggering actions in other systems — in the hands of end users, Google is keeping the keys with technical teams who manage company infrastructure.
That's a deliberate contrast to how most competitors play this market. Microsoft Copilot Studio and ServiceNow's AI tooling both lead with low-code interfaces designed so a marketing manager or HR coordinator can build agents without filing a ticket. Google's approach centralizes that work in IT.
The Case For IT-First Control
There are real reasons to want it this way. Agents that can access internal data, send emails, or interact with business systems are a security surface — and giving every department self-service access to build them is how you end up with a rogue sales agent querying customer records it shouldn't touch. IT-controlled deployment means tighter permissions, better audit trails, and agents that actually connect to the right systems instead of requiring workarounds.
For organizations already running on Google Workspace and Google Cloud, the integration case is also cleaner. Gemini-powered agents can sit close to the data rather than requiring connectors and middleware to bridge everything together.
The Tradeoff Is Real
Centralizing through IT means bottlenecks. If a content team needs an agent to format weekly reports and the IT queue runs six weeks long, they will build something themselves using whatever tools they can access — which is exactly what shadow IT looks like. Google's bet here is that enterprises have matured enough to want governance over speed. That may be true for regulated industries like finance and healthcare. It's a harder sell for fast-moving teams who measure productivity in hours, not quarters.
The platform is geared for technical users specifically, which means non-developers won't be evaluating it themselves — this decision lands on IT leaders and engineering managers. For them, the question isn't whether the Gemini models are capable; it's whether centralizing agent-building through their department is a model the rest of the organization will actually accept.