Google Cloud unveils persistent Gemini Agents for long-running tasks, and they get their own Gmail, Calendar, and Drive storage

Google is unveiling a new universal AI agent for the workplace that can research information, create documents, write code, coordinate other AI agents and complete tasks lasting hours or days — all while maintaining the same memory, business context and identity across different applications and devices.

Announced Thursday at the company's Gemini at Work 2026 event, the new Gemini agent represents Google's attempt to turn its enterprise AI offering from a collection of assistants and specialized tools into a unified platform capable of taking on entire assignments.

Rather than asking users to manage separate agents for different tasks, Google wants employees to delegate objectives to one agent that figures out how to complete them, accesses the necessary enterprise systems and returns finished work.

For existing customers, Google says the agent will operate through Gemini Enterprise and familiar workplace interfaces, including Google Workspace, Microsoft 365 and Slack, rather than requiring employees to use a dedicated application.

Google's existing Gemini Enterprise service is accessible through web and mobile apps, but the company has not specified exactly how customers activate the new universal agent or when all its capabilities will become available.

The architecture is also notably flexible when it comes to AI models: while Google supplies its own Gemini models, the agent can already use Anthropic's Claude models, with support for additional proprietary and open-weight AI models planned.

The announcement arrives amid an intensifying contest to provide the central AI interface for enterprise work. On September 25, Microsoft introduced an updated Copilot combining productivity work, software development and persistent automation. Four days later, OpenAI introduced its own always-on dots agents. And on October 6, Anthropic announced native Claude integration with Google Docs, Sheets and Slides, allowing users to edit Workspace files directly through Claude or access Claude inside Google's productivity applications.

Another competitor, SpaceXAI, introduced its persistent Grok Bot agents in August and expanded the offering with shared Team Bots in September. These competing announcements illustrate a broader shift: AI companies increasingly want their assistants to become long-running digital workers, not merely chatbots that respond to individual prompts.

AI coworkers get their own email addresses, calendars and permissions

The universal Gemini agent can work in different configurations, including as an individual employee's personal assistant or as a persistent digital coworker with responsibilities shared across a team.

According to Google Cloud CEO Thomas Kurian's announcement, the Gemini agent operates through a common interface and API, with access extending across the web, iOS and Android devices, Windows and Mac computers, command-line tools, Google Workspace, Microsoft 365 and Slack.

The coworker setup is particularly notable because Google intends to give these agents their own identities within an organization's existing productivity infrastructure.

For example, a manager could create a Gemini 'Event Planner Agent' that receives its own Workspace account, email address, calendar, Drive storage and company-directory presence.

Employees could then assign work to the agent much as they would to a colleague, including by mentioning it in Google Chat or requesting document edits.

Because execution takes place in the cloud, employees can start an assignment on one device, leave it running and resume from another without reconstructing the context.

Google says the agent can manage workflows lasting multiple days, coordinate parallel assignments and respond to scheduled tasks or events. It can also assemble temporary groups of specialized sub-agents for complex work, distributing different responsibilities among them.

Google's announcement does not establish that every instance of the universal Gemini agent must have a separate Workspace account. Rather, the dedicated account is described as part of one configuration.

Carefully limited access to information, but questions remain

The company didn't specify in embargoed materials shared with VentureBeat ahead of the public unveiling whether administrators can selectively enable or disable individual components of a Gemini agent's Workspace presence, or exactly how provisioning and licensing will work.

These distinctions matter because an employee using Gemini to complete a one-time assignment may have very different identity, security and administrative requirements from a business department deploying an AI agent that functions as a permanent member of its team.

Google says each agent receives a cryptographically attested identity and permissions managed through enterprise security systems. Its actions are recorded in audit logs, including when it creates isolated environments to execute code.

An Agent Gateway enforces organization-wide policies on communications between agents and external systems, while sandboxing provides boundaries around code execution.

Crucially, Google says coworker agents can access only information that team members explicitly share with them, rather than inheriting a human employee's entire collection of permissions.

That distinction could be important for organizations considering AI agents that operate across sensitive financial records, customer databases, legal documents and internal communications.

One agent for research, documents, coding and longer-running work

The system's memory architecture spans four categories: session memory for ongoing tasks, semantic memory for accumulated knowledge, procedural memory for learned workflows and episodic memory covering previous work.

These are intended to help the agent develop an understanding of a company's processes, employees and institutional knowledge instead of requiring users to explain the same information repeatedly.

To connect that intelligence with actual business operations, Google supports tools including Salesforce, ServiceNow, Jira, Git, BigQuery, Snowflake, Databricks and Microsoft Teams. Enterprises can also connect Model Context Protocol (MCP) servers and publish reusable instructions and tools to shared internal registries.

The promise is that an employee could ask Gemini to research market trends, build a financial model using company data and produce an accompanying presentation without separately directing every step.

Google has not supplied independent comparative benchmarks demonstrating how reliably the new agent completes such lengthy, cross-application assignments.

How Google's Gemini agent compares with Microsoft Copilot, OpenAI, Anthropic and Grok Bot

Google's announcement follows several developments from competitors pursuing similar goals, although their approaches differ in model selection, application integration and how agents operate independently.

Microsoft's new Copilot, introduced September 25, is particularly close to Google's vision. Its Home interface combines conversational assistance with delegated work through Cowork, while Code allows employees to create applications and automations. The new Autopilot agent can continue working in the background, monitor conversations and maintain its own identity, memory and workspace. Microsoft is rolling out Home and Code through its Frontier program, while Autopilot is expanding through private preview.

OpenAI's Dots agents, introduced at DevDay on September 29, similarly take on ongoing responsibilities, operate across connected applications and continue progressing between user interactions. ChatGPT Space also provides shared project context and collaboration capabilities.

Anthropic, meanwhile, is pursuing deeper integration into existing productivity applications. Its Claude for Google Workspace offering, announced just two days before Google's event, allows users to read and edit Google Docs, Sheets and Slides through a sidebar, while connectors allow Claude to create and modify those files from its own interface. The announcement concerns Claude's broader Workspace integration, rather than a feature exclusive to its Claude Code programming product.

Another particularly relevant competitor is SpaceXAI, whose Grok Bot product launched August 11 as a collection of persistent AI workers with their own cloud computers. As VentureBeat reported at the time, users can assign jobs to individual Bots, give them access to software applications and websites, and allow them to continue operating after the user's computer is turned off. Grok Bot can also learn recurring workflows and coordinate assignments among multiple agents.

SpaceXAI expanded those capabilities on September 28 with Team Bots, a shared-agent offering designed for organizations. Teams can configure agents with common files, applications, skills and organizational knowledge, then interact with them individually or through Slack. The system maintains shared knowledge while keeping individual conversations private. Team Bots is currently available in public beta on Teams and Enterprise plans.

The similarities between Google's digital coworkers and Grok Bot's team agents are striking: both envision named, persistent AI workers that maintain context, interact with employees and operate across business systems over time.

One technical distinction is that Grok Bot emphasizes operating software through a dedicated computer environment, including applications without suitable APIs, while Google highlights integrations, reusable skills, agent identities and security controls built into its enterprise platform.

Google's support for Claude is especially notable because it suggests enterprises could retain the same agent infrastructure, company context and reusable skills while changing the models performing individual tasks. Microsoft also supports multiple models and automatic model selection, making this an emerging area of competition rather than a capability exclusive to Google.

Google adds cost controls and specialized industry agents

Google is also emphasizing the operational economics of increasingly autonomous AI.

A new Smart Routing capability selects models for individual workloads based on performance and cost, potentially allowing companies to reserve more expensive models for difficult tasks.

Google also highlighted project-level spending limits that can pause agent activity when budgets are exhausted, along with the ability to attribute costs to individual departments.

However, spend caps themselves are not entirely new: Google announced hard project-level spending limits in August, alongside pay-as-you-go options and savings plans offering 10% or 20% discounts for one-year or three-year commitments, respectively.

Google has not announced a separate price for the universal Gemini agent or specified whether every capability will be included in existing Gemini Enterprise subscriptions.

Nor has the company provided a general-availability date or comprehensive rollout schedule for the new capabilities. Although Google's existing Gemini Enterprise app offers web and mobile access, the announcement does not establish when customers can begin using the new universal agent, provision persistent digital coworkers or take advantage of its full cross-platform features.

Those unanswered questions make it difficult for enterprise buyers to assess the immediate cost and practical requirements of deploying Google's proposed digital workforce.

Beyond general-purpose agents, the company is introducing specialized capabilities for data engineering, business analytics, finance and legal work.

Financial Services, currently in preview, includes more than 50 foundational skills and connections to financial information providers including FactSet and LSEG. The Legal offering focuses on document-management permissions and confidentiality requirements, with support for platforms including NetDocuments and iManage.

Google cites substantial adoption of its existing Gemini Enterprise products, reporting that nearly 90% of Fortune 100 companies use the platform. Among its examples, BNP Paribas is deploying Gemini Enterprise to more than 65,000 employees, while Japanese insurer SOMPO has built more than 10,000 custom agents. Those deployments do not necessarily represent adoption of the new universal agent.

For enterprise technology leaders, the larger question is whether a single AI system can reliably handle work spanning multiple applications, sensitive data sources and extended periods without introducing unacceptable security, operational or financial risks.

Google's announcement provides an ambitious architecture for addressing those challenges. But questions remain about feature availability, real-world reliability and the costs of operating persistent agents at scale.

The competition increasingly centers not only on which company offers the most capable AI model, but on which platform enterprises trust to coordinate their work — even when the underlying models come from competitors.