Stop Running 10 AI Pilots. Start With One Platform That Actually Works.
Google just launched Gemini Enterprise as a centralized AI platform. Here's how it compares to Microsoft Copilot and what to pilot first.
Google’s Gemini Enterprise: a real front door for AI at work
You know the feeling. Ten AI pilots running in ten corners of the company. Cool demos. Little change. What’s missing is a single place where people can ask for help, pull context from your systems, and get work done start to finish.
That’s what Google says it shipped with Gemini Enterprise on October 9, 2025. It’s a centralized AI platform: one chat entry point, prebuilt agents you can use on day one, a visual builder to create your own, connections into your core systems, and governance in one console. Think less toolbox, more operating layer.
What’s actually new
Prebuilt and custom agents. Google is offering a set of out-of-the-box agents for deep research, data analysis, and common business tasks. You can also compose your own with a no-code builder.
Real enterprise connectors. Gemini Enterprise can pull context from Google Workspace, Microsoft 365, Salesforce, SAP, and more, then act inside those workflows.
One place to govern. You get a central view to secure, audit, and manage agents across the organization.
Partner network and standards. Google is leaning into an “agent economy” with a finder to discover agents and support for open protocols like MCP and proposed agent-to-agent patterns.
Separate from “Gemini for Workspace.” This lives under Google Cloud as a platform, not just a feature inside Docs or Gmail. Early customer logos are already showing up. Published pricing starts near $30 per user per month, with a lower Business tier in some coverage.
A side note you’ll hear in the halls: Gemini 3. There’s broad chatter about a near-term release. Treat it as a likely upgrade path rather than a promise on a calendar.
Why this matters now
Most firms don’t lack AI features. They lack flow. People copy-paste between chatbots, spreadsheets, CRMs, and knowledge bases. If Gemini Enterprise works as advertised, it reduces that friction by grounding agents in your systems and letting those agents run multi-step processes under one roof. That’s the leap from “summarize a doc” to “open the case, pull the contracts, draft the amendment, route it for approval, and log the activity.” Less swivel-chair. More outcomes.
And the positioning is clear: a single front door for AI at work. That clarity matters. It gives IT and business leaders one place to point employees, one model to train, one security pattern to review.
How it compares to Microsoft’s Copilot stack
Where Microsoft is strong
Deep app embed. Copilot is threaded through Teams, Outlook, Word, Excel, and PowerPoint. Grounding via Microsoft Graph keeps answers inside your tenant context.
Agent creation with guardrails. Copilot Studio lets you build agents and govern them with admin policies. There are role settings, content filters, and approval flows.
Connectors galore. Microsoft has a large catalog for services like ServiceNow and Salesforce and the ability to build your own.
Computer use. For legacy systems without APIs, Copilot can drive clicks and keyboard actions to complete tasks.
Where Google now looks stronger
One coherent entry point. Google’s story is simpler: single chat, prebuilt agents, builder, connectors, and governance in one place. Microsoft’s offer can feel split across Copilot Chat, Microsoft 365 Copilot, and Copilot Studio, with different licenses and capacity add-ons.
Cross-suite neutrality. Google is explicit about working well with both Workspace and Microsoft 365. Helpful if you’re hybrid.
Agent marketplace motion. The agent finder suggests faster time to value for common use cases.
Licensing reality check
Microsoft 365 Copilot remains about $30 per user per month for eligible plans. Building and running agents can involve Azure and metered usage, which adds budgeting variables.
Google lists Gemini Business at $21/seat/month and Gemini Enterprise Standard/Plus at $30/seat/month. Validate current packaging with your rep. This category moves fast.
Risks and tradeoffs
Name changes and product consolidation. This market is moving quickly. Keep your internal docs current so people know what to buy, what to deploy, and where to get support.
Governance maturity. Both vendors promise central control. Kick the tires on audit logs, agent permissions, data boundaries, and incident response before rollout.
Hidden costs. Agent usage, connectors, and model upgrades can shift spend. Set budgets and alerts early.
What to do Monday morning
Pick two workflows that drive revenue or reduce cycle time. For example, renewals desk or intake triage. Write the steps on one page.
Map the data. List which records live in Microsoft 365, Salesforce, Drive, or SharePoint. Decide the minimum connectors you need.
Pilot one platform as your home base. If you’re already deep in Microsoft 365 and want minimal change, start with Copilot plus Studio. If you need a cleaner front door across mixed stacks, trial Gemini Enterprise. Time-box the pilot to six weeks.
Measure actual outcomes. Minutes saved per case, cycle time, conversion rate. No metrics, no expansion.
Decide your agent strategy. Use prebuilt agents when they’re good enough. Build custom agents where your process is your edge. Lock down governance before you scale.
Bottom line: if Google delivers on the “single front door,” it gives enterprises a credible alternative to Microsoft’s inside-the-apps approach. The pragmatic move is simple. Choose one to be primary, prove value on a revenue-adjacent workflow, then scale.
Moving Forward with Confidence
The path to responsible AI adoption doesn’t have to be complicated. After presenting to nearly 1,000 firms on AI, I’ve seen that success comes down to having the right framework, choosing the right tools, and ensuring your team knows how to use them effectively.
The landscape is changing quickly - new capabilities emerge monthly, and the gap between firms that have mastered AI and those still hesitating continues to widen. But with proper policies, the right technology stack, and effective training, firms are discovering that AI can be both safe and transformative for their practice.
Resources to help you get started:
In addition to publishing thought AI leadership on a regular basis, I also work directly with firms to identify the best AI tools for their specific needs, develop customized implementation strategies, and, critically, train their teams to extract maximum value from these technologies. It’s not enough to have the tools; your people need to know how to leverage them effectively.
For ongoing insights on AI best practices, real-world use cases, and emerging capabilities across industries, consider subscribing to my newsletter. While I often focus on legal applications, the broader AI landscape offers lessons that benefit everyone. And if you’d like to discuss your firm’s specific situation, I’m always happy to connect.
Contact: steve@intelligencebyintent.com
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