Google Brings Agentic AI to Gemini for Businesses
Google says Gemini can work across Gmail, Drive, Docs, Sheets, Slides, Chat, and Calendar. It also connects to external platforms such as Microsoft 365, Slack, Jira, Salesforce, and ServiceNow.
Moreover, Gemini can coordinate specialist sub-agents for complex assignments. These agents can handle separate stages of a task and then combine their work into a final result. The system can continue running in the cloud after users close their devices.
Google is also introducing persistent coworker agents with their own identities and email addresses. These agents can take on defined team roles, such as project coordination or financial analysis. However, their access depends on permissions and the information an organisation provides.
Model Choice, Security and Enterprise Controls
Another key feature is model flexibility. Gemini selects a suitable model for each task, including Google’s Gemini models and Anthropic’s Claude models. Google also plans to add more private and open models.
At the same time, Google is adding controls for enterprise security, governance, and spending. These include authorisation policies, secure execution environments, model routing, and real-time spending limits. Consequently, businesses can manage costs and permissions as they expand their use of AI agents.
Google is also introducing specialised capabilities for financial services and legal teams. These tools can support investment research, risk analysis, legal document review, and contract workflows. Meanwhile, data teams can use natural-language requests to generate code, troubleshoot pipelines, and produce operational reports.
Businesses Get First Access
Google is prioritising enterprise customers before expanding agentic capabilities to consumers. The company says nearly 90% of Fortune 100 businesses already use Gemini Enterprise, giving it an established corporate user base.
Early testers include sportswear company On, Shopify, and PayPal. Their use cases include speeding up product operations, combining AI models, and routing requests across different systems. However, wider adoption will depend on how reliably these agents perform complex tasks.
The launch places Google in direct competition with other companies developing autonomous AI assistants. Across the industry, providers are moving beyond chat interfaces toward agents that can plan work, use software, and complete multi-step assignments.
Ultimately, Google’s approach makes Gemini a shared interface for workplace AI tasks. If the system can deliver reliable results while maintaining security and cost controls, it could change how businesses organise everyday work. Nevertheless, companies will need to assess accuracy, oversight, data access, and accountability before assigning agents sensitive responsibilities.
