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Google's Gemini Agent for Work: A Universal Enterprise Agent That Uses Gemini and Claude
Google Cloud unveiled Gemini agent at Gemini at Work 2026: an enterprise agent that takes objectives, works across Workspace and third-party tools, and routes jobs to Gemini or Claude models.
At its Gemini at Work 2026 event on 8 October, Google Cloud announced Gemini agent, which it calls a "single, universal agent for work." It is one of the clearest signs yet that enterprise AI is moving from chat assistants to agents that complete work.
What Gemini agent does
Google's pitch is simple: "give it objectives, not instructions." According to the announcement, the agent can:
- Answer questions and handle knowledge work
- Create media
- Write and run code
- Work across the Gemini Enterprise app, Google Workspace and third-party services
Users can call it with an @Gemini mention inside Gmail, Docs, Sheets, Slides and Chat. Google also mentioned surfaces including the command line, Slack and Microsoft 365, and an API that lets it run as a "headless agent" inside other systems.
Multi-model by design
The most interesting detail for technology leaders: the agent runs "each job on the model that fits best," including Gemini and Claude model families today, with other private and open models planned. A major cloud provider building its flagship enterprise agent around more than one model family is a strong signal that model choice is becoming a feature, not a risk.
Memory
Google described four types of memory — session, semantic, procedural and episodic — so the agent can remember context within a task, facts about your work, how you like things done and what happened previously.
Availability
At announcement, Gemini agent was in private preview, with Google saying it would see wide availability soon for Workspace customers on select Business and Enterprise plans. No pricing was stated.
What this means for businesses
If you are on Google Workspace
Expect agentic features to arrive inside the tools your teams already use. Start thinking now about which workflows you would trust an agent with, and what approvals you need.
If you build internal tools
The headless API matters. Agents that can be embedded into your own systems make it possible to automate multi-step work without building everything from scratch — but they need well-designed APIs and permissions to act on.
Governance comes first
An agent that can act across email, documents and third-party tools needs clear boundaries:
- Least-privilege access to data and actions
- Approval steps for anything that sends, pays or deletes
- Audit logs of every action
- Clear policies on which data agents may use
See our guides to AI agent risks and writing an AI acceptable use policy.
The bigger picture
Google, Microsoft, OpenAI and Anthropic are all converging on the same idea: AI that takes goals and completes work across your tools. The winners inside companies will be teams that prepare their data, APIs and governance early.
Our AI agent development team helps businesses design and govern agents across Google, Microsoft and custom platforms.