Google Unveils Persistent Gemini Agents for Long-Running Tasks

At its recent Gemini at Work 2026 event, Google Cloud announced the introduction of persistent Gemini agents, designed to handle long-running tasks and maintain a consistent memory architecture across different applications and devices.

These universal AI agents can research information, create documents, write code, coordinate other AI agents, and complete tasks lasting hours or days, all while maintaining their identity and business context.

The new 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.

Instead of 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.

The universal Gemini agent will operate through Gemini Enterprise and familiar workplace interfaces, including Google Workspace, Microsoft 365, and Slack, without 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 of the persistent agents is flexible in terms of 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.

This flexibility allows organizations to choose from a range of models that best suit their needs, rather than being locked into a specific model or vendor.

The announcement arrives amid an intensifying contest to provide the central AI interface for enterprise work. Microsoft introduced its updated Copilot combining productivity work, software development, and persistent automation in September, while OpenAI introduced its own always-on Dots agents around the same time.

Anthropic announced native Claude integration with Google Docs, Sheets, and Slides on October 6, 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.

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 can 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, respond to scheduled tasks or events, and assemble temporary groups of specialized sub-agents for complex work.

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.

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 persistent agents compare with Microsoft Copilot, OpenAI, Anthropic, and Grok Bot is a topic of interest. Each company is pursuing similar goals, although their approaches differ in model selection, application integration, and how agents operate independently.

Microsoft’s new Copilot 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.

OpenAI’s Dots agents 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 is pursuing deeper integration into existing productivity applications through Claude for Google Workspace, which 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.

SpaceXAI’s Grok Bot product launched in August as a collection of persistent AI workers with their own cloud computers. 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.

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. 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.

The company 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.