- Google's platform for creating and orchestrating AI agents with integration into corporate data
- Key components: Gemini models, no-code editor, governance, and secure connectors
- Plans starting at $21 (Business) and $30 (Enterprise) per user per month
- Real-life examples and ecosystem: Virgin Voyages, Gap, Figma, Klarna, and over 100.000 partners
The race to bring artificial intelligence agents into everyday work has entered a new chapter. Google has announced Gemini Enterprise, an enterprise platform that allows any team to design, deploy, and coordinate agents capable of handling entire processes, not just individual tasks.
The proposal brings together the generative models of the Gemini family and enterprise tools in a single conversational environment, with direct integration to the organization's data and a no-code visual editor. The focus is clear: to accelerate automation with centralized control, security, and governance , with plans starting at $21 and $30 per user per month depending on the option.
What is Gemini Enterprise and how is it structured?
At its core, the platform combines the latest Gemini multimodal models (text, image, and video) with a vertical architecture design built on Google TPUs. The company argues that this combination of chips, models, and agent layer enables more consistent and higher-performing operations at an enterprise scale.
The service is structured in five parts. First, Brains , which provides reasoning and content generation based on Gemini models. Second, Workbench , a no-code environment for business professionals to analyze information and automate workflows without programming.
Third, Taskforce , a fleet of pre-built and customizable agents that perform specialized tasks. Fourth, Context , which securely connects to sources such as Google Workspace, Microsoft 365, Salesforce, and SAP. And fifth, Governance , a framework for auditing, securing, and monitoring all deployed agents.
Catalog of agents, use cases and tools
From the outset, Gemini Enterprise includes pre-configured agents for tasks such as in-depth research, trend analysis, performance reporting, and onboarding, as well as connectors to enterprise systems (Salesforce, SAP, Jira, and Microsoft 365). The goal is to cover common needs without starting from scratch.
Google has shown practical examples, such as Virgin Voyages ' marketing assistant nicknamed "Email Ellie", which has helped increase monthly sales by 28% and cut campaign creation time by 40% through a coordinated flow of agents for research, strategy and content.
Among the new features, the company is previewing a Data Science Agent (currently in private preview) that automates data preparation and ingestion and generates multi-step plans for training and inferring models, reducing manual tuning. The Customer Engagement Suite is also being enhanced with a low-code visual builder for deploying omnichannel conversational agents.
In the area of productivity, Gemini Enterprise integrates Google Vids to create videos from text or presentations, and in Google Meet it incorporates real-time voice translation preserving tone and intent , designed for meetings between global teams.
Interoperability, payments between agents and ecosystem
To facilitate cross-system collaboration, Google is promoting the Agent2Agent protocol , announced at its I/O conference, which aims to enable agents from different companies (even with different models) to collaborate securely . The company will also expand the Gemini CLI with new extensions and support for a curated catalog in the AI Agent Finder.
A key differentiator is the Agent Payments Protocol (AP2) , developed in partnership with PayPal and Mastercard, designed to enable secure transactions between agents . This opens up possibilities for business automation that go beyond simple queries or content generation.
Google emphasizes that its ecosystem comprises over 100.000 technology partners , facilitating the integration of vertical solutions that have been evaluated for security and interoperability. This network reinforces the concept of a platform, not just a set of tools.
Security and control for corporate environments
The governance component is cross-cutting: organizations can monitor the behavior of each agent, enforce access and audit policies, and maintain regulatory compliance from a unified dashboard. This layer aims to give CIOs and security managers confidence when scaling AI.
Furthermore, the connection to corporate data is carried out under principles of least privilege and traceability , integrating with the most used office suites and CRMs without needing to move information outside of repositories already approved by the company.
Early customers and results
Beyond Virgin Voyages, Google cites Gap, Figma, Klarna, Macquarie Bank, and Gordon Food Service as early adopters. The case studies presented focus on analytics automation, report generation , and building customer service agents, with deployments aimed at achieving a measurable impact on efficiency and quality.
The promise is to allow each employee to have an assistant tailored to their role, with the ability to access data, perform tasks, and coordinate with other agents, all within a corporate security perimeter.
Prices, availability and return calculation
Gemini Enterprise comes with two plans: Gemini Business , geared towards small teams or SMEs, starting at $21/user/month , and Gemini Enterprise for large organizations, starting at $30/user/month . It is available globally in markets where Google Cloud operates.
The cost prompts some calculations: in an organization with 1.000 employees, the annual bill would be around $360.000, depending on the chosen plan. Google is accompanying the launch with materials to estimate the return on investment, focusing on time savings and improved conversion rates in business cases.
Competitors and market timing
Google's move comes at a time when Microsoft Copilot has become firmly established in Office 365 and Azure, and OpenAI is driving the enterprise version of ChatGPT. According to IDC, Copilot accounts for a significant portion of generative AI implementations in North American and European companies.
Consulting firms foresee fertile ground: Gartner estimates that investment in enterprise AI will reach $320.000 billion by 2026, while McKinsey projects cost reductions of 15-20% and productivity increases of up to 30% in administrative areas thanks to intelligent agents.
Training and programs to accelerate adoption
To facilitate implementation, Google is launching Google Skills , a free platform with approximately 3.000 courses that brings together training from across the company (including content from Google DeepMind and Grow with Google). The stated goal is to train one million professionals in agent creation.
Alongside this, initiatives such as Gemini Enterprise Agent Ready (GEAR) to train developers, Gemini Agent Foundry with community-oriented hackathons and marketplace, and Delta , a team of Google Cloud engineers that temporarily integrates into organizations to address complex cases, are being launched.
With this launch, Google aims to position Gemini Enterprise as a comprehensive platform that combines models, tools, security, and ecosystem to scale agents. Market interest and initial results suggest that the key will be the speed with which pilot projects can be transformed into sustained impact on processes, costs, and customer experiences.
