The struggle to carry the artificial intelligence agents Adds a new chapter to daily work. Google has announced Gemini Enterprise, an enterprise platform that enables any team to design, deploy, and coordinate agents capable of covering entire processes, not just individual tasks.
The proposal brings together the generative models of the Gemini family and corporate tools in a single conversational environment, with direct integration to the organization's data and a code-free visual editor. The focus is clear: accelerate automation with control, security and centralized governance, with plans from $21 to $30 per user per month depending on the option.
What is Gemini Enterprise and how is it structured?
At the technical core, the platform combines the latest Gemini multimodal models (text, image, and video) with a vertical architecture design based on Google's TPUs. The company argues that this combination of chips, models, and agent layers allows for enterprise-scale operations with greater consistency and performance.
The service is divided into five blocks. First, Brains, which provides reasoning and content generation from Gemini models. Second, Workbench, a no-code environment for business profiles to analyze information and automate flows unscheduled.
Third, Taskforce, a fleet of pre-built, customizable agents that perform specialized tasks. Fourth, Context, which securely connects to sources such as Google Workspace, Microsoft 365, Salesforce, or SAP. And fifth, Governance, a framework for auditing, protecting and monitoring all deployed agents.
Catalog of agents, use cases and tools
From the start, Gemini Enterprise incorporates preconfigured agents for tasks such as in-depth research, trend analysis, performance reporting, and onboarding, as well as connectors to enterprise systems (Salesforce, SAP, Jira, or Microsoft 365). The goal is to cover common needs without starting from scratch.
Google has shown practical examples, such as the marketing assistant of Virgin voyages nicknamed “Email Ellie,” which has helped increase monthly sales by 28% and cut campaign creation time by 40% through a coordinated flow of agents to research, strategy and content.
Among the new features, the company advances a Data Science Agent (in private preview) that automates data preparation and ingestion and generates multi-step plans for training and inferring models, reducing manual tuning. It also evolves the Customer Engagement Suite with a low-code visual builder to deploy omnichannel conversational agents.
In the area of ​​productivity, Gemini Enterprise integrates Google Videos to create videos from text or presentations, and in Google Meet it incorporates real-time voice translation while preserving tone and intention, designed for meetings between global teams.
Interoperability, payments between agents and ecosystem
To facilitate work between systems, Google promotes the protocol Agent2Agent, announced at its I/O, which seeks to enable agents from different companies (even with different models) to collaborate safelyThe firm will also expand Gemini CLI with new extensions and support for a curated catalog in the AI Agent Finder.
A differential piece is the Agent Payments Protocol (AP2), developed together with PayPal and Mastercard, aimed at enabling secure transactions between agentsThis opens up opportunities for commercial automation that go beyond simple querying or content generation.
Google emphasizes that its ecosystem exceeds the 100.000 technology partners, which makes it easier to incorporate vertical solutions evaluated for security and interoperability. This network reinforces the idea of ​​a platform, not just a set of tools.
Security and control for corporate environments
The governance component is transversal: organizations can monitor behavior of each agent, apply access and audit policies, and maintain regulatory compliance from a unified panel. This layer seeks to give confidence to CIOs and security officers when it comes to scaling AI.
Furthermore, the connection to corporate data It is carried out under the principles of least privilege and traceability, integrating with the most widely used office suites and CRMs without having to move information outside of the company's already approved repositories.
Early customers and results
Beyond Virgin Voyages, Google cites Gap, Figma, Klarna, Macquarie Bank and Gordon Food Service among the early adopters. The cases shown revolve around analysis automation, report generation and building customer service agents, with deployments that seek a measurable impact on efficiency and quality.
The promise is to allow every employee to have a adapted assistant to its function, with the ability to access data, execute 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, aimed at small teams or SMEs, from $21/user/month, and Gemini Enterprise for large organizations, from $30/user/monthAvailability is global in the markets where Google Cloud operates.
The cost invites to do the math: in an organization of 1.000 employees, the annual bill would be around 360.000 dollars depending on the plan chosen. Google accompanies the launch with materials to estimate the return, focusing on time saved and conversion improvement in commercial cases.
Competitors and market timing
Google's move lands in an environment where Microsoft Copilot has been consolidated in Office 365 and Azure, and OpenAI ChatGPT is promoting its enterprise version. According to IDC, Copilot accounts for a significant portion of generative AI implementations in companies in North America and Europe.
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 the intelligent agents.
Training and programs to accelerate adoption
To make getting started easier, Google is launching Google Skills, a free platform with around 3.000 courses that aggregates training from across the company (including content from Google DeepMind and Grow with Google). The stated goal is train a million professionals in agent creation.
Along with this, initiatives such as Gemini Enterprise Agent Ready (GEAR) to train developers, Gemini Agent Foundry with community-oriented hackathons and marketplaces, and Delta, a team of Google Cloud engineers temporarily integrated into organizations to address complex cases.
With this launch, Google is trying to position Gemini Enterprise as a comprehensive platform that combines models, tools, security, and an ecosystem to scale agents. Market interest and early results suggest that the key will be speed in converting pilots into sustained impact on processes, costs and customer experiences.
