Google's Agent Push

Google used its Cloud Next conference on April 22 to launch Gemini Enterprise Agent Platform, a new system for building and managing corporate AI agents. (cloud.google.com) Google says the platform folds Vertex AI’s model and agent tools into one stack with new controls for integration, orchestration, security, DevOps and monitoring. The company described it as the next step for organizations moving from a few pilots to fleets of production agents. (cloud.google.com) (blog.google) In Google’s documentation, the platform is positioned around four jobs: build, scale, govern and optimize. Google also introduced Agent Studio for low-code development and an upgraded Agent Development Kit for code-first teams. (docs.cloud.google.com) (cloud.google.com) An AI agent is software that can search company data, make decisions and carry out multi-step work with limited human prompting. Google’s pitch is that large companies now need one place to track which agents exist, what data they can reach and how they are performing. (docs.cloud.google.com) (blog.google) That problem has grown as Google has widened Gemini Enterprise beyond chat-style assistants into a broader workplace system. Google now says Gemini Enterprise includes prebuilt connectors for apps such as Confluence, Jira, Microsoft SharePoint and ServiceNow, plus support for custom agents. (docs.cloud.google.com) (cloud.google.com) Google is also pushing an open-ecosystem argument. Its Gemini Enterprise app says customers can use Google-made, third-party and custom agents in one interface, and it points to the Agent2Agent protocol as a way for agents built on different systems to communicate. (cloud.google.com) Accenture tied itself more closely to that strategy the same day. On April 22, Accenture and Google Cloud announced a Gemini Enterprise Acceleration Program that combines Google Cloud engineering, Google DeepMind models and Accenture industry teams to deploy specialized agents for clients. (newsroom.accenture.com) Google framed the launch as a management issue as much as a model issue. Sundar Pichai said the question has shifted from whether companies can build an agent to how they can manage “thousands of them,” and Google’s answer is a centralized control layer inside Gemini Enterprise. (blog.google) The immediate test is whether large companies want one vendor to sit across model choice, app access, security controls and agent deployment. Google is betting that the harder part of the next AI phase is not making another agent, but keeping all the agents inside one governed system. (cloud.google.com) (docs.cloud.google.com)