Gemini Enterprise Agent: Delegate Work Across Apps Now
See how Gemini Enterprise uses persistent memory and AI agents to delegate multi-step work across Workspace, Microsoft 365, and Slack.
8 ott 2026 (Aggiornato il 8 ott 2026) - Scritto da Christian Tico
Source: Google.
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Google’s Gemini Enterprise Agent: AI That Delegates Work Across Workspace, Microsoft 365, and Slack
Google is positioning Gemini Enterprise as more than a workplace chatbot. Its newly announced Gemini agent is designed to take on multi-step tasks, coordinate specialized sub-agents, and work across Google Workspace, Microsoft 365, Slack, and other business tools. Google says the agent can retain context between sessions and channels, so employees can delegate work without repeatedly explaining the background. The offering is currently in private preview, with wider availability planned for eligible Workspace customers.
What Is Google’s Gemini Enterprise Agent?
The Gemini Enterprise agent is a unified AI agent for business tasks such as researching information, answering questions, creating content, writing code, and coordinating workflows. Rather than limiting interactions to a standalone chat window, Google says people will be able to reach the agent through familiar work environments and devices.
The goal is to let employees hand off an outcome, not just ask for a one-off answer. Depending on the task, the agent may work across connected company data and applications, carry out multiple steps, and continue working in the cloud after the initial request.
How Gemini Works Across Google Workspace, Microsoft 365, and Slack
Google says Gemini can connect with business applications including Google Workspace, Microsoft 365, and Slack. The wider Gemini Enterprise platform also supports integrations with services such as Jira, GitHub, Salesforce, and ServiceNow. This cross-platform approach is intended to help teams work with information wherever it is stored, rather than moving everything into a single suite.
- Google Workspace: Gemini can work with productivity apps such as Gmail, Drive, Docs, Sheets, Slides, Chat, and Calendar.
- Microsoft 365: The platform can connect with Microsoft tools and data, giving organizations another way to use Gemini alongside their existing productivity environment.
- Slack: A Slack integration can let Gemini search connected messages and files, with links back to the relevant Slack content.
Connections to company systems require deliberate configuration. Google describes the platform as working with business data under security controls and existing permissions, but organizations should confirm which sources are enabled and what access the agent receives before using it for sensitive work.
Persistent Memory for Ongoing Work
A central part of Google’s pitch is persistent context. Because the agent runs in the cloud, Google says it can carry relevant task context across devices and supported channels, instead of treating every conversation as a fresh start.
Google describes four memory types:
- Session memory: Information related to an active task, including work that may continue over an extended period.
- Semantic memory: Structured knowledge gathered from documents and conversations.
- Procedural memory: Information about how recurring work or processes are completed.
- Episodic memory: Records of prior actions and completed assignments.
Persistent memory could make handoffs smoother for long-running assignments, but it also makes governance important. Businesses will need clear policies for retention, access, sensitive information, and how employees review or correct information the agent uses.
Sub-Agents Can Divide Complex Assignments
For more complicated requests, Google says Gemini can coordinate specialized sub-agents. These agents can handle separate parts of a task, either in sequence or in parallel, before contributing to a broader result. This could help with work that involves gathering information, analyzing it, and preparing a deliverable.
Google has also described persistent coworker agents with their own identities and storage. According to the company, these agents should only access context that users or teams make available to them. Organizations will want to understand the setup and access model before assigning them ongoing responsibilities.
What Businesses Should Consider Before Adopting It
Cross-app AI agents may reduce repetitive work, but organizations should assess the practical details before relying on them for important workflows. Consider the following questions:
- Which applications and data sources are connected, and who can authorize those connections?
- Do permissions in each system carry through to the agent’s searches and actions?
- Can employees review, approve, or reverse consequential actions?
- How are persistent memory and task records managed?
- What human checks are needed for sensitive, regulated, or customer-facing work?
These questions matter because an agent that can act across several applications needs clear boundaries. A useful rollout should start with well-defined, low-risk workflows and include monitoring, employee training, and a process for handling errors.
Availability and What Is Still Unclear
Google’s announcement describes the Gemini agent as being in private preview, with broader availability planned for select Workspace Business and Enterprise customers. That means organizations should distinguish announced capabilities from features they can use today. Availability, supported integrations, and exact controls may vary as the product develops.
Businesses evaluating the agent should verify current eligibility, supported applications, security documentation, and preview limitations with Google before planning a deployment.
Conclusion
Google’s Gemini Enterprise agent points toward a workplace AI that can retain context, delegate parts of a task to sub-agents, and operate across Workspace, Microsoft 365, Slack, and other connected services. If the announced capabilities work reliably in practice, they could make it easier to delegate multi-step knowledge work. For now, the product remains in private preview, so businesses should evaluate its access controls, memory governance, and human approval requirements as carefully as its potential productivity benefits.
The hardest part of a persistent workplace agent may not be getting it to remember, it may be deciding what it should forget. Once memory spans apps, teams, and time, governance becomes part of the product’s intelligence: stale or mis-scoped context can turn yesterday’s convenience into tomorrow’s automated mistake.
How do sub-agents work in Google's Gemini Enterprise platform?
