Google Cloud Next Google has overhauled its enterprise AI strategy in the wake of the agentic push across the biz landscape, rebranding and expanding its Vertex AI developer platform into what it now calls the Gemini Enterprise Agent Platform.

It comes as the challenge facing businesses has shifted from building individual AI agents to managing hundreds or thousands of them at once - something Workday and others are trying to tackle too.

"The early versions of AI models were really focused on answering questions that people had and assisting them with creative tasks. Now we’re seeing as the models evolve people wanting to delegate tasks and sequences of tasks to agents," Google Cloud CEO Thomas Kurian told reporters during a press briefing. "And these agents then being able to turn around and use a computer, use all of GCP and Workspace as a tool."

To meet the moment, Google rolled out infrastructure in the form of its eighth generation of TPU chips and security updates through its purchase of Wiz.

Those announcements as well as the Gemini Enterprise Agent Platform are designed to give companies a single system for developing, deploying, governing, and monitoring AI agents across their organizations. Google says it can act as the connective layer between a company's data, its employees, and the growing fleet of autonomous agents that enterprises are beginning to rely on.

"All the pieces are designed to do this," Kurian said in the briefing. "The security to protect these agents. Our data cloud to feed the agents context from within the system. Our AI infrastructure to optimize performance, scale and cost of how agents run. This year is the next evolution of where we see this AI technology going."

He said organizations are choosing Google Cloud because of its ability to deliver "a comprehensive backbone for innovation" rather than "individual services that can be cobbled together."

Gemini Enterprise Agent Platform is organized around four pillars: build, scale, govern, and optimize. On the build side, Google introduced Agent Studio, a low-code interface for creating agents using natural language, alongside an upgraded Agent Development Kit with a new graph-based framework for orchestrating multiple agents working together, the company said during a media prebriefing.

It also provides an agent registry that gives organizations a central catalog of each internal agent and tool, the company said. Also inside the new platform is an agent marketplace that offers pre-built agents from partners including Atlassian, Oracle, ServiceNow, and Workday.

The platform includes Agent Runtime, a feature that Google says delivers sub-second cold starts and gives users the ability to provision new agents in seconds. It also supports long-running agents — autonomous processes that can operate for hours or days on complex business workflows like financial reconciliation or sales prospecting. A new Memory Bank feature gives agents persistent, long-term memory across sessions rather than starting from scratch each time, the company said.

But it is the governance capabilities that may matter most to enterprise buyers who fear that AI tools may proliferate across their organizations with limited oversight. Agent Identity assigns every agent a unique cryptographic ID with defined authorization policies, creating an auditable trail of every action, Google said. Agent Gateway, meanwhile, acts as the police for agent ecosystems, enforcing security policies and protecting against prompt injection, tool poisoning, and data leakage. An Agent Anomaly Detection system flags suspicious behavior by analyzing the intent behind agent actions, and gives users the chance to stop it before it goes rogue.

Then there are the ways Google has said its tools can be used to fine-tune agents, such as Agent Simulation for stress-testing them against synthetic interactions before deployment. Agent Evaluation scores live performance, while Agent Observability dashboards trace execution paths and diagnosing problems in real time for rapid debugging, the cloud giant told reporters.

Google said the Gemini Enterprise app — the consumer-facing side of the platform — is a place where non-technical employees can build and manage their own agents using Agent Designer.

Users can create schedule- or trigger-based agents to automate multi-step processes, while an "Inbox in Google Enterprise gives those users a central hub for monitoring agent activity with notifications sorted into categories like "Needs your input," "Errors," and "Completed."

Google CEO Sundar Pichai said, based on internal adoption statistics, there is evidence of a shift toward agentic workflows. He said 75 percent of all code at Google is now AI-generated and approved by engineers, up from 50 percent last (northern hemisphere) fall. In a blog, he described a recent internal code migration completed by agents and engineers working together that "was completed six times faster than was possible a year ago with engineers alone."

Its tools are surging in popularity, Google claims, with nearly 75 percent of its Cloud customers using AI products, while Gemini Enterprise saw 40 percent growth in paid monthly active users quarter over quarter in Q1, and Google's first-party models now process more than 16 billion tokens per minute via direct API use, up from 10 billion the prior quarter.

There also appears to be a lot of token-maxxing among customers. Google said 330 Google Cloud customers each processed more than one trillion tokens, while 35 reached the 10-trillion-token milestone with its models.

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Within the press material for the show, several large customers provided testimonials about their own Gemini deployments. GE Appliances said it has more than 800 of Google's AI agents running across manufacturing, logistics, and supply chain operations. KPMG reported 90 percent Gemini Enterprise adoption among employees with more than 100 agents deployed in the first month. Tata Steel said it deployed over 300 specialized agents in nine months. Merck announced a partnership valued at up to $1 billion to build an agentic platform across its R&D, manufacturing, and commercial functions.

The announcements land in an increasingly competitive market for enterprise AI platforms. Microsoft, Amazon Web Services, and Salesforce have all made a push into agent orchestration and management in recent months. Google's approach leans heavily on vertical integration, with the hope that designing chips, models, infrastructure, and application layers together produces better results than assembling components from different vendors.

Google also announced a $750 million fund to support its partner ecosystem in building and deploying agentic AI, along with agreements with McKinsey, Deloitte, and other consulting firms that will receive early access to upcoming models from Google DeepMind. ®

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