Google unveils Gemini Enterprise to manage AI agents at scale
Google Cloud launches end-to-end agent platform at Next ’26 to help enterprises build, govern, and scale AI agents!
AI agents are everywhere. Managing them is where things start to break. At its Next ’26 event on 22 April 2026, Google Cloud introduced an expanded Gemini Enterprise. The goal is to bring models, tools and governance into a single system that enterprises can actually control. Here's how it works!
From fragmented tools to a unified system
Until now, building AI agents meant stitching together multiple layers. Teams relied on different tools for models, orchestration, monitoring and security, which made scaling messy. Gemini Enterprise is designed to simplify that.
It brings these layers together into one stack that handles the full lifecycle, from development to deployment. This matters because agent sprawl is becoming real. As organisations experiment, they end up with dozens or even thousands of agents running without clear oversight.
The three pillars behind Gemini Enterprise
Google has structured the platform into three key layers that work together. The first is the Agent Platform, which evolves from Vertex AI. This is where developers build, train and manage agents using models and orchestration tools.
The second is the Gemini Enterprise app. It serves as a workspace where employees can create, run, and share agents without requiring deep technical expertise. Moreover, the third is the ecosystem layer.
Integrations with platforms like Salesforce, Oracle, ServiceNow, Adobe and Workday allow organisations to plug in third-party agents directly. Together, these layers create a controlled but flexible environment.
What the Agent Platform actually adds
The Agent Platform introduces capabilities across building, scaling, governance and optimisation. For development, a new Agent Development Kit enables teams to create networks of agents and manage workflows through graph-based orchestration. This makes it easier to handle complex, multi-step tasks.
For scaling, the platform includes a more advanced runtime. Agents can persist, delegate tasks and maintain long-term context using features like Memory Bank and Memory Profiles. Governance is where Google is placing heavy emphasis.
Systems like Agent Identity and Agent Gateway help track, control and secure agent behaviour across environments. On the optimisation side, tools such as Agent Simulation and Observability allow teams to test and monitor performance before and after deployment.
Making AI usable beyond engineering teams
The Gemini Enterprise app is where the platform becomes accessible. Users can build workflows using a no-code Agent Designer, track processes through an Inbox system and maintain shared context using Projects. This makes it easier for non-technical teams to participate in automation.
The app also includes a collaborative Canvas for working across Google Docs and Slides. It supports exporting to Microsoft 365 formats, which helps it fit into existing enterprise workflows. Adoption depends on usability, and this layer is clearly designed to expand access beyond developers.
Why governance is at the centre of this launch
As AI agents scale, control becomes more important than capability. Google is positioning Gemini Enterprise as a system where governance is built in from the start. Features like cryptographic identities, policy-based access and security safeguards aim to reduce risks such as prompt injection and data leakage.
According to Thomas Kurian, this approach supports the transition to what he describes as an “agentic enterprise”. In other words, automation at scale, but with oversight intact.
The rise of an enterprise agent ecosystem
Another important piece is distribution. Through an Agent Gallery inside the platform, organisations can discover and deploy third-party agents. These are accessed via Google Cloud Marketplace and go through approval workflows before being used.
This creates a marketplace model for AI agents. Instead of building everything internally, companies can adopt pre-built solutions that meet their needs while staying within governance frameworks.