Gemini Enterprise wins top AI agents rating for universities

Gemini Enterprise for Education has been named a Commander in The Tambellini Group's 2026 StarChart for AI agents for administrative efficiency, with the product ranked first for innovation and usability, according to Google.

The classification is the highest in the analyst group's assessment of agent platforms for higher education administration. Google presented the result as recognition for a product that combines its Gemini models with agent-building tools, search functions, governance controls and Google Cloud infrastructure.

Tambellini's report said the platform stood out for bringing several elements together in one environment rather than offering a single-purpose application. It added that this approach could appeal to institutions seeking to avoid managing separate tools for different AI tasks.

Google highlighted a passage from the report that said: "Gemini Enterprise for Education is differentiated by how much it brings together in one place. It combines Gemini models, agent-building tools, enterprise search, governance controls, and Google Cloud infrastructure in a single environment. For institutions that do not want to manage a mix of disparate tools, this creates a clearer path to building and managing AI services at scale."

Campus operations

Google said the product is designed for administrative use across business, academic and research functions at universities and colleges. Potential uses include advising, student support and service operations, with AI agents handling multi-step workflows that would otherwise require manual intervention.

It also pointed to no-code tools for simpler agents and a software development path for more complex deployments. The emphasis reflects a wider push by technology suppliers to embed generative AI into routine university processes, from support desks to internal knowledge systems.

According to excerpts cited by Google, the platform is meant to sit within a broader cloud environment rather than operate as a standalone higher education application. The report said this provides "a familiar foundation for building conversational and agent-based services that can work across different interfaces, data types, and connected systems."

Data access

A key area of focus is how AI agents connect to institutional data. Google said agents can be grounded in productivity tools, content repositories, databases and data platforms including BigQuery, while enterprise search and research tools can help users find and synthesise information across internal sources.

This has become a central issue for higher education buyers as institutions weigh how to apply AI to admissions, enrolment, student retention and research administration without losing control of sensitive data. Governance and auditability have emerged as key requirements as universities test generative AI products for staff and student use.

Google said the platform includes administrative controls, permission inheritance, role-based access, logging and Model Armour. Those features are intended to help institutions manage access, oversight and data protection within the same environment.

Customer examples

Google cited the University of California, Riverside and Purdue University as examples of institutions using its education AI tools. At UC Riverside, Gemini Enterprise for Education has been used as a unified portal for agent experiences across a campus community of 25,000 students, faculty and staff, according to Google.

For Purdue, Google linked the platform to a broader institutional AI strategy spanning teaching, research and campus operations. The university is using Google Cloud technology to support collaboration, automate operational tasks and expand AI-enabled education, Google said.

The higher education sector has become an important test case for large technology groups seeking to show practical uses for generative AI beyond consumer chatbots. Universities combine administrative complexity, large user populations and varied data environments, making them a target market for suppliers pitching AI systems that can work across departments.

Tambellini's assessment, as cited by Google, said simpler agents can be created through no-code tools, while more advanced use cases can be built through the Agent Development Kit and Agent Runtime.