Author: Prashanth Ashwathram: Vice President- Technology
For years, building an AI agent was an engineering project. That era is closing. Google's Gemini Enterprise Agent Platform, and its low-code studio in particular, lets a finance manager or an operations lead stand up an agent without writing a line of code. The instinct is to cheer the volume: More builders, more agents, more automation. Volume is not a victory, and it can quietly become liability. Building an agent used to be the finish line; Now it is the starting gun. When anyone can build one, you do not get a single, well-governed system; You get dozens, each made by someone with their own idea of what it may touch. The question that matters is not how many agents you can build. It is which ones you can trust, and how you scale the ones that work.
The tension shows up in the numbers. McKinsey's research on the state of AI finds that while 62 percent of organizations are at least experimenting with AI agents, only 23 percent have scaled an agentic system anywhere in the enterprise. Most companies can already make agents; Very few have made them dependable enough to run the business on. A low-code platform lifts the first figure. It does nothing, on its own, for the second. That gap between building and trusting is a business problem, not a build problem, and it is where real work now lives.
In April 2026, Google made the Gemini Enterprise Agent Platform generally available, the successor to what used to be called Vertex AI, organized around four plain ideas: Build, scale, govern, and optimize.
Build is the headline, because a low-code canvas takes agents out of the engineering queue. Govern is the part that decides outcomes, and Google invested there: An agent can be given a verifiable identity, catalogued, and held inside guardrails, so the organization can see what each one is and what it may do. On maturity, the foundation is ready today, since agent identity is generally available, while several governance and quality tools are still arriving in preview.
The intent is clear: Make agents easy to create and possible to control on the same platform.
Guardrails enforce the rules you set. They do not set them. Two questions stay firmly with the business:
Answer the first well and you avoid the failure that makes headlines. Answer the second well and a promising pilot becomes enterprise value. Neither is a technology setting; Both are judgment, applied the same way every time. That discipline is exactly what KPI Partners builds into IQ Foundry, our governed, domain-expert agents.
Some leaders already run a handful of agents; a few built by eager teams, perhaps more than they can easily name. That is not something to hide; It is a head start, if you act on it. The organizations already feeling the sprawl are the closest to needing an operating model and the best placed to install one. The goal is not to stop people building. It is to give them a governed path, so that what they build can be trusted and scaled instead of quietly stacking up risk.
Through IQ Foundry, KPI Partners delivers governed, domain-expert agents across functions like finance, supply chain, and procurement, built from the outset to discuss, decide, act, and scale, with guardrails, role-based access, human oversight, and a full audit trail.
As part of our agentic AI practice, and through the Enterprise AI Lab, we help you decide what each agent should be trusted to do, tie it to outcomes you can measure, and scale only the ones that earn it, on the platform you already run, including Google Cloud. Google supplies the machinery; We bring the operating model and the accountability that turn many agents into a few you can rely on.
Now that anyone can build an agent, having built one is no longer a distinction, and having built a hundred is not a strategy. The advantage goes to the organizations disciplined about trust, deliberate about scale, and clear about accountability, so that a smaller set of agents does real work, dependably. Google made building easy for everyone. Choosing what to trust, and scaling it well, is what separates a drawer full of pilots from a business that actually runs on agents.