Gemini Enterprise
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Last reviewed
May 31, 2026
Sources
21 citations
Review status
Source-backed
Revision
v1 ยท 2,268 words
Add missing citations, update stale details, or suggest a clearer explanation.
Gemini Enterprise is Google's enterprise AI platform, announced on October 9, 2025, that the company describes as the new front door for AI in the workplace. It brings together Google's Gemini models, a no-code workbench for building and orchestrating AI agents, a set of prebuilt Google agents, connectors to data held in systems like Google Workspace and Microsoft 365, and a central governance layer, all reached through a single chat interface. The platform repackages and supersedes Google's earlier Agentspace offering, and Google positions it against Microsoft 365 Copilot and Salesforce Agentforce in the contest to put AI agents in front of office workers.[1][2][3]
Google Cloud CEO Thomas Kurian and Alphabet CEO Sundar Pichai introduced the product at a company event called Gemini at Work, held on Google's campus. Pichai framed the launch in terms of moving past simple chatbots toward software that can act on a person's behalf, while Kurian set out the technical pieces in a companion post on the Google Cloud blog. The pitch is that an employee in any department, not just engineering, can ask questions of company data and then hand work to agents that carry out multi-step tasks such as creating a calendar event, updating a ticket, or pulling together a research brief.[1][2][4]
The simplest way to describe Gemini Enterprise is as a chat application that sits on top of a company's information and a library of agents. A worker types a request in plain language, the system grounds its answer in the organization's documents and applications, and where the request calls for action rather than an answer, the platform routes it to one or more agents. Google calls this single entry point a front door, the idea being that staff no longer need to know which underlying tool or model handles a given job.[1][3]
That framing is also a strategy statement. Google Cloud spent 2024 and 2025 shipping a stack of agent building blocks, including the models themselves, the Agent Development Kit, the Agent2Agent protocol for agents talking to each other, and Vertex AI for model tuning and deployment. Gemini Enterprise is the layer that packages those pieces for buyers who want a finished product rather than a toolbox. Kurian summarized the shift by saying that Vertex AI had evolved into what Google now calls the Gemini Enterprise Agent Platform, the home for building, scaling, governing, and optimizing an agentic workforce.[1][5]
Google's launch post lists six core components that the platform unifies.[1]
The first is the Gemini models, which Google calls the brains of the system. These are the same frontier models that power Google's consumer Gemini app, and the platform also reaches related models for media generation such as the Imagen image model and the Veo video model.[1][6]
The second is a no-code workbench. Through it, a person in marketing or finance or any other team can analyze information and assemble agents that automate a process, without writing code. Google's editor for this is called Agent Designer, which carried over from Agentspace.[1][7]
The third is a set of prebuilt Google agents. At launch these included a Deep Research agent for gathering and synthesizing information, a Data Insights agent, and a Data Science agent in preview that automates data wrangling and ingestion. Customers can add their own custom agents alongside these.[1][6]
The fourth is the data connectors. Google says the platform securely connects to company data wherever it lives, naming Google Workspace, Microsoft 365, Salesforce, and SAP, along with other business applications such as Box. This cross-vendor reach is one of the points Google leans on when it contrasts itself with rivals tied to a single suite.[1][3]
The fifth is a central governance framework. From one place, administrators can see, secure, and audit every agent in use. The platform gives each agent an identity and routes its activity through policy and logging controls, which is meant to answer the obvious worry about turning autonomous software loose on corporate systems.[1][7]
The sixth is the partner ecosystem. Google cites more than 100,000 partners and a discovery surface, sometimes called the Agent Gallery or AI Agent Finder, where buyers can browse agents from Google, from their own organization, and from outside vendors that have passed security and interoperability review. Google said roughly 1,500 agents were available at launch, with partner agents coming from companies including Adobe, Salesforce, ServiceNow, and Workday.[1][8][16]
Gemini Enterprise is the successor to Google Agentspace. Agentspace launched in December 2024 and gained wider attention with updates at Google Cloud Next in April 2025, where Google described it as something like a search bar for enterprise data, connecting to applications such as SharePoint, Salesforce, Drive, Slack, and Jira and adding a no-code Agent Designer and Google-built agents for deep research and idea generation.[9][10]
When Gemini Enterprise arrived, Google folded Agentspace into it rather than running the two side by side. Reporting at the time described Gemini Enterprise as a rebranded and expanded version of Agentspace, and the Agentspace web address began redirecting to the Gemini Enterprise page.[3][11] Google has said the conversational and orchestration technology from Agentspace forms the core of the new platform, now combined with newer models and more built-in agents. For customers, Google set out a migration path: Agentspace stops being available for new subscriptions at the end of 2025, while existing subscribers keep their features, pricing, and support until their contract renews, at which point the plan moves to Gemini Enterprise.[12]
Google launched Gemini Enterprise with tiered, per-seat pricing. The entry tier, Gemini Business, is aimed at small businesses and startups, and the Standard and Plus tiers target larger organizations that need stronger IT controls and governance. A Frontline edition is positioned for large field teams in sectors like retail and logistics, where workers mainly use agents that an administrator has already provisioned; Google offers it as an add-on that requires a minimum number of Standard or Plus seats. The Business tier comes with a 30-day free trial. Reported prices vary by commitment length and by source, and Google notes that heavy use of AI features can draw additional compute charges from a linked Google Cloud account on top of the per-user fee.[11][13][14]
| Edition | Reported price per user per month | Intended for |
|---|---|---|
| Gemini Business | About $21 with an annual commitment | Small businesses and startups |
| Gemini Enterprise Standard | About $30 with an annual commitment | Larger organizations needing IT controls |
| Gemini Enterprise Plus | Around $50 and up | Organizations needing the fullest feature set and governance |
| Frontline | Add-on requiring a minimum number of Standard or Plus seats | Large field and deskless teams using prebuilt agents only |
Google said the platform was available globally at launch, in the countries where Google Cloud products are sold, and pointed to compliance certifications that include authorization for use by United States government agencies. Because pricing and edition details shift over time, the figures above should be read as the launch-window reporting rather than a fixed rate card.[11][13][14]
Gemini Enterprise enters a market that Microsoft and Salesforce reached first. Microsoft sells Microsoft 365 Copilot as an add-on to its Office subscriptions, commonly cited at $30 per user per month, and its advantage is depth inside applications that millions of people already open every day. The trade-off observers point to is reach: Copilot lives most naturally within the Microsoft suite, and pulling in data from Salesforce, Jira, or SAP tends to require custom connector work. Salesforce Agentforce comes at the problem from its customer data, building agents directly into the Salesforce CRM and running them on what the company calls its Atlas Reasoning Engine, which makes it strong for customer-facing jobs anchored in CRM records.[15][16][17]
Google's counterargument rests on three claims: that Gemini models bring a large context window and native handling of text, images, audio, and video; that the connectors reach across vendors, including into Microsoft 365 itself; and that the governance layer treats agents from many sources under one policy model. Whether those advantages outweigh the incumbents' installed base is the open question, and several analysts noted that Google arrived after Microsoft and OpenAI had already been selling to the same buyers.[15][16][18]
| Platform | Vendor | Anchored in | Cited entry price |
|---|---|---|---|
| Gemini Enterprise | Gemini models plus cross-vendor connectors | About $21 to $30 per user per month | |
| Microsoft 365 Copilot | Microsoft | The Microsoft 365 application suite | About $30 per user per month |
| Agentforce | Salesforce | The Salesforce CRM and its data | Usage and consumption based |
Google named a long list of early customers at launch. Virgin Voyages said it had deployed more than 50 agents to handle operational tasks, and used Google's media models to produce large volumes of personalized advertising. Best Buy reported a 200 percent increase in customers who rescheduled deliveries on their own and resolved 30 percent more questions on topics like price matching and recycling. Other names Google cited include Klarna, Commerzbank, HCA Healthcare, Figma, Mercedes-Benz, Macquarie Bank, Gordon Foods, GAP, Signal Iduna, and Banco BV, with use cases ranging from contact-center automation to relationship management to a nurse handoff tool in healthcare.[1][2][6]
The broader significance is what the launch signals about Google Cloud's direction. By consolidating its scattered agent tools into one product with a recognizable name, Google moved its enterprise pitch from individual features toward a single platform that competes head to head with Microsoft and Salesforce. The launch sat alongside related announcements, including open protocols for agents to communicate and to transact, a free training hub called Google Skills, and a program to help developers build on the platform, which together read as an attempt to make Gemini Enterprise the default surface for AI work inside Google Cloud customers.[1][2]
The most common criticism at launch was timing. Google brought Gemini Enterprise to market after Microsoft and OpenAI had spent more than a year selling enterprise AI, so it has to win share rather than define the category. Gartner analyst Joe Mariano offered a measured read, saying he did not believe the platform would accelerate agentic AI adoption on its own while granting that it offered greater extensibility than what was on the market. A separate worry was naming churn across the field; Gartner's Matt Cain argued that frequent renaming of AI products adds to market confusion rather than clarity, a remark that landed on the Agentspace-to-Gemini-Enterprise rebrand itself. Coverage also raised the familiar concern about concentration, since putting documents, search, and agents into one vendor's cloud deepens reliance on Google, which the company tries to soften with its cross-vendor connectors.[3][18][21]
The technology carries the limits of the models underneath it. For regulated or high-stakes work such as legal review, compliance, or financial reporting, a general-purpose model can hallucinate, behave inconsistently, and be hard to audit, which is why many deployments lean on retrieval from trusted sources to keep answers grounded. Security is a live issue as well. In December 2025 researchers at Noma Security disclosed a flaw they called GeminiJack, an indirect prompt-injection weakness in which a booby-trapped document, calendar invite, or email could plant hidden instructions that made Gemini Enterprise search for sensitive terms and leak the results, with no click required from the victim. Google fixed it by changing how Gemini Enterprise and Vertex AI Search interacted with their retrieval systems. That episode, along with an earlier vulnerability reported in a Gemini email-summarization feature, underlines how a platform built to read and act on company data widens the surface that attackers can probe.[19][20]