Google is intensifying its push into enterprise AI with Gemini Enterprise, a subscription service aimed at bringing AI agents into the daily workflows of corporate employees.
The launch, which follows OpenAI’s new third-party app integrations and Amazon Web Services’ Quick Suite announcement, marks Google’s most comprehensive attempt yet to turn its AI research into practical business value.
Gemini Enterprise, which starts at $30 per user per month, is designed for large organisations, while Gemini Business, at $21 per user monthly, serves smaller clients.
Both plans allow companies to create and deploy AI agents that can draw on data from tools such as Box, Microsoft 365, and Salesforce.
These agents can automate tasks, surface insights, and support workers across departments – all without requiring coding expertise.
“Gemini Enterprise is designed on the premise that true business transformation in the era of AI must go beyond simple chatbots,” said Sundar Pichai, CEO, Google.
“You need a comprehensive and integrated platform that brings all your company’s data, tools, and people together in one secure place.
That’s exactly what we’ve built. Gemini Enterprise is an AI-powered conversational platform designed to bring the full power of Google AI to every employee for every workflow.”
The introduction of Gemini Enterprise underscores how quickly AI agents are moving from research labs into business operations. For IT leaders, the implications are significant: the product aims to offer a secure, governable framework for rolling out AI capabilities across large organisations, while maintaining compliance and oversight – two long-standing challenges in enterprise AI adoption.
A Platform Built for IT Governance and Security
Google has positioned Gemini Enterprise as more than a productivity assistant.
At its core, it is an AI orchestration platform – a way for IT departments to manage, deploy, and monitor AI agents safely across complex corporate environments.
One of its key features, Model Armor, automatically inspects and filters potentially unsafe or noncompliant prompts and responses within AI interactions.
This layer of protection allows companies to deploy AI tools at scale without the risk of data leaks or regulatory violations. It also eliminates the need for IT teams to build their own content moderation or data security layers, reducing deployment time and complexity.
For IT leaders, Model Armor could be a pivotal feature, allowing them to confidently expand AI access to more teams and departments while maintaining centralised control.
From Centralised IT to Distributed Intelligence
Gemini Enterprise represents a philosophical shift for enterprise IT: rather than acting as gatekeepers of technology, IT leaders can become enablers of AI-driven innovation across the business.
Because Gemini’s tools require no coding, departments such as marketing, finance, or HR can independently create agents for specific workflows.
For instance, an HR team could build an agent that answers policy questions or drafts onboarding materials, while a finance team could automate forecasting reports by connecting Gemini to real-time spreadsheets and analytics dashboards.
IT retains control through centralised policies, data permissions, and monitoring, ensuring that corporate governance frameworks remain intact. In practice, Gemini Enterprise could allow organisations to balance creativity and control – enabling bottom-up experimentation within a top-down structure of security and accountability.
Automating Development and Data Workflows
Beyond business operations, Gemini Enterprise has clear applications for software development and data science.
Google includes prebuilt agents designed specifically for these technical functions, providing IT departments with ready-to-use accelerators.
Developers can use Gemini to generate, review, and optimize code in real time, while data scientists can leverage Gemini to automate tasks such as dataset preparation, model monitoring, and report generation.
This kind of automation could help IT departments address two persistent pain points: talent shortages and growing workloads. By embedding AI copilots directly into development environments, organisations can reduce time-to-deployment and improve productivity without expanding headcount.
Competing Visions for the AI-Driven Enterprise
Google’s move comes as competition in enterprise AI intensifies. OpenAI recently introduced new ChatGPT capabilities that let users access third-party tools, while Amazon Web Services announced Quick Suite, a no-code agent builder integrated with over 50 business applications.
Each of these offerings targets a similar goal: to democratise AI development and give organisations practical ways to automate knowledge work.
Where Google aims to differentiate itself is through its full-stack AI infrastructure – from its proprietary Tensor Processing Units (TPUs) and Gemini models to integrated tools for compliance and security.
Its no-code approach could also reduce the barriers to entry for business units, while governance features like Model Armor help IT maintain compliance and oversight.
If successful, the product could redefine the role of IT within organisations – from maintaining systems to orchestrating an intelligent, distributed network of AI agents that operate safely within enterprise boundaries.
