Unify AI With Gemini Enterprise

Just 18 months ago, many organizations weren’t using any artificial intelligence tools at all. Fast forward to today, and many are already tipping into AI sprawl, with too many tools, too much overlap, too few training resources and too little ROI.

Add in the emergence of agentic AI, and many business and IT leaders are feeling pressure to show measurable results, even as they chase down instances of shadow IT and try to sort out hype from reality.

Google Gemini Enterprise, which debuted late last year, gives organizations a hub that centralizes AI workflows, provides secure access to enterprise data, and simplifies the deployment and adoption of AI agents.

Here’s a three-step process for getting the greatest value from the platform.

Out of the box, Gemini Enterprise acts like a general expert agent, powered by Google Gemini and based on Google’s Vertex AI platform. This is the default experience if users simply log in and start querying.

However, the real value starts to show when organizations connect Gemini Enterprise to other popular enterprise systems that store valuable data: SharePoint, Salesforce, Outlook, OneDrive, ServiceNow, Google Drive, Box and many more. These integrations are typically quick and easy, and once they’re in place, organizations can search across their data silos with a single query and have it reason and act. Gemini Enterprise respects existing permissions, so users only see the data they’re entitled to, and they can toggle a switch to eliminate outside information from the web — ensuring that answers are based on validated internal information.

Users might use Gemini Enterprise to check the status of tasks in project management platforms, check equipment maintenance logs or pull sales data, all from one central platform.

This is where the synthesis and analysis happen. Here again, users’ workflows will look fairly similar to their use of stand-alone AI tools from Google, such as Gemini or NotebookLM. Typically, they will ask Gemini Enterprise to find trends or connections in the data.

The difference is that Gemini Enterprise can ground these capabilities in internal business data, producing insights that are more relevant and actionable. For example, the platform might generate an at-a-glance view of progress across multiple projects, create a prioritized plan for equipment maintenance or identify common sales support issues.

At this stage, Gemini Enterprise moves beyond search and synthesis to take real steps inside enterprise systems, turning insights into outcomes. Gemini Enterprise offers prebuilt agents for common tasks such as drafting documents and responding to customer emails, and it features a low/no-code agent designer that allows users to create their own simple automations.

For more complex custom agents, developers can leverage the Gemini Enterprise agent development kit, and administrators can publish and manage a catalog of approved agents to give users safe, standardized options. In practice, this might mean using Gemini Enterprise to automatically generate a sales proposal, update the status of a service ticket or schedule equipment maintenance follow-up tasks.

That’s the real value of Gemini Enterprise: It helps enterprises rein in their AI sprawl while paving the path to the technology’s next frontier.