Gemini at Work 2026: Introducing Gemini agent | Google Cloud Blog
Short summary
Google Cloud is launching Gemini Agent, a unified AI assistant that handles knowledge work, content creation, coding, and task automation across enterprise systems. It works persistently in the cloud, maintains context across devices and apps, and can orchestrate multiple sub-agents to complete complex workflows.
- Gemini Agent operates as a single interface for work—you assign objectives rather than give instructions, and it completes tasks across Gmail, Drive, Docs, Sheets, and other Workspace apps while maintaining memory and context across devices
- The agent uses multi-model orchestration (Gemini models plus Claude and others) with smart routing and cost controls, automatically selecting the best model for each task rather than always using the largest one
- It connects to enterprise systems (Salesforce, ServiceNow, BigQuery, Git, Jira, etc.), learns from reusable skills and tools stored in company registries, and can spawn temporary sub-agents or persistent "coworker agents" with their own identities to coordinate multi-step workflows
- Early customers like Bradesco cut document review time from 1 hour to 5 minutes and achieved 10% financial efficiencies; BNP Paribas deployed it to 65,000 employees for streamlined workflows
Full summary
Google Cloud is launching Gemini as a unified agent designed to handle most work tasks from a single interface—answering questions, managing knowledge work, creating images and media, and writing code. The agent maintains persistent memory across devices and channels (web, mobile, desktop, Slack, Microsoft 365, command line), so you don't have to re-explain context or wonder which machine you assigned a task to. It connects to your existing systems like Salesforce, ServiceNow, BigQuery, Databricks, Git, Jira, and Confluence, and can operate as either a personal assistant or a team member with its own persistent identity and email address. Google Cloud says nearly 80% of their customers now use their AI products, and 90% of the Fortune 100 use Gemini Enterprise, suggesting these tools have moved beyond experimentation into actual business operations.
The agent's architecture rests on several technical choices. Gemini can dynamically create sub-agents to handle multi-step workflows running in parallel or sequentially over hours or days. It selects the best model for each task—drawing from Google's Gemini family, Anthropic's Claude, and other models—rather than defaulting to the largest one, which improves accuracy on complex problems while cutting costs on simpler ones. The system learns from every interaction, building a personalization graph that improves over time. Early customers like On (the sportswear brand), Shopify, and PayPal have tested these capabilities; Shopify uses multi-model blending for millions of merchants, while PayPal routes 10 million multi-model requests weekly.
Gemini's power comes from three components: tools that connect to your software stack, skills that are modular sets of instructions teaching the agent how your work actually gets done, and context that lets it remember. Google offers an enterprise tools registry where teams can build and share custom tools, plus a global library of skills with company-specific and personal skill registries. The announcement emphasizes security through identity management, authorization controls, sandboxing, and network gateways, along with cost controls via smart routing and real-time spend caps. The agent can be deployed as a headless service without a dedicated interface, meaning it integrates into whatever applications you already use.