Google Cloud unveils the Gemini agent, which can handle multiday enterprise workflows in Workspace, Microsoft 365, and Slack using Gemini and other AI models

Your existing work tools now have an AI agent that can complete multi-day tasks across different platforms without you needing to switch applications.

Google Cloud has introduced a new AI agent called Gemini, designed to handle complex, multi-day enterprise workflows. Announced at Gemini at Work 2026, this agent integrates with existing business systems, including Google Workspace, Microsoft 365, and Slack. Gemini aims to consolidate tasks from knowledge work and content creation to coding, all accessible through a single prompt interface. It intelligently selects the most appropriate AI model for each task and includes features for cost control, security, administration, and governance, addressing key enterprise requirements. The agent can execute planned work, utilize various tools, and deliver completed outputs directly within users' existing work environments like documents and inboxes.

The Gemini agent represents a significant step towards more integrated and autonomous AI assistants in the enterprise, moving beyond simple chatbots to orchestrators of complex business processes. By unifying access to various AI models and business systems, Google Cloud is attempting to create a seamless experience that reduces context switching and boosts productivity for knowledge workers and developers alike. Its focus on enterprise-grade security and governance suggests a strategic push to capture large organizations hesitant about adopting AI due to compliance and control concerns.

This development positions Google Cloud as a direct competitor in the burgeoning field of AI-powered workflow automation, challenging established players and signaling a future where AI agents are deeply embedded in daily operations. The ability to handle multiday workflows across disparate platforms like Microsoft 365 and Slack indicates a strategy to abstract away integration complexities for businesses, potentially lowering the barrier to AI adoption for more intricate tasks. It will be crucial to observe how Gemini's performance, cost-effectiveness, and integration capabilities stack up against emerging alternatives.