For several months, Gemini Enterprise (formerly Agentspace) has been a dominant talking point in the Google Cloud Ecosystem. We’ve written before about what Gemini Enterprise is, and what some of the benefits are. The question we then get asked most often is: how do I start taking advantage of it?

It’s not necessarily a trivial question. Many organizations are running pilots of Gemini Enterprise to see what it can do. But they don’t always have much to show for it. Of course this isn’t just an Gemini Enterprise problem - according to a 2025 MIT Media Lab study, 95% of enterprise AI pilots fail to deliver measurable ROI. But it’s also not NOT an Gemini Enterprise problem.

In this article we’ll talk about the most common pitfalls we’re seeing preventing organizations from implementing impactful solutions using Gemini Enterprise, and propose a framework for identifying and scoping high-ROI Gemini Enterprise use cases.

Why Do So Many Pilots Fail?

By far the most common problem when building pilots (in Gemini Enterprise or otherwise) is building something no one actually wants to use. Again, this isn’t just an Gemini Enterprise issue, but it’s endemic in piloting AI solutions like these.

The issue is starting with what the technology can do, rather than what the end user wants or needs. In other words, the demos show the potential of the tech, but don’t necessarily map to an identified use case.

There can be several reasons for this:

• They are solutions looking for a problem. The senior leadership gives IT a mandate to “become AI driven.” The team then does what it knows, starting with the technology first and worries about the problem to be solved second.
• Technologists and engineers might implicitly understand or be able to envision the possibilities, and assume business stakeholders will as well.
• Far too few organizations have a discipline of interviewing front-line team members. And so they aren’t close enough to the problems those team members have. The result is senior leaders specifying use cases but not mapping them to the actual needs of their team.
• The same MIT research found the majority of AI budgets were being directed toward sales and marketing pilots. Yet they found the biggest ROI was typically in the less glamorous but more effective back-office automation.
• There is an amplification of flawed processes. Whenever you do automation you implicitly are doing workflow design. And the rules that apply to a manual process don’t always apply to an automated one. Ideally you use that as an opportunity to redesign the workflow itself, in ways that make sense given the new technology available. Otherwise you either turn a good process into a bad one, or magnify an already broken process.
• Most pilots aren’t integrated with other systems in the business. Understandable, since it’s just a pilot, and integration can be messy and expensive. But it can dramatically limit what those pilots can do.

The 3 Traits of High-ROI Gemini Enterprise Use Cases

So how do you address these issues, and find Gemini Enterprise pilots that actually have a high likelihood of success? From what we’ve found, the use cases that consistently deliver measurable returns share three defining characteristics. They are:

1. High-Context
2. High-Frequency
3. High-Friction

High-Context

High-Context means there is a rich amount of data that Gemini Enterprise can actually pull from. An agent that doesn’t need much proprietary data to do its job is limited in its usefulness, as it is not much different than a generic LLM like ChatGPT. However, you have to actually be able to access that data to make it useful, even in the pilot phase.

One reason we love Gemini Enterprise is because it addresses the the high-context problem. Because of the extensive network of out-of-the-box connectors, you’re able to provide the pilot more data-rich context than you typically would otherwise.

Any process that requires workers to use multiple systems to piece together information represents a big opportunity, as Gemini Enterprise is designed explicitly to connect over 100 enterprise systems together. Use cases might include:

• A PE firm building a dashboard to consolidate financial, sales, and operational data.
• A healthcare provider identifying at-risk reimbursements by aggregating payer, billing, and claims data.
• A manufacturer bringing together supply-chain and inspection data to automate compliance reporting.

High-Frequency:

A workflow that is useful when needed but is only needed intermittently is of limited benefit. You ideally want to be solving things that frustrate your customers or your team on a consistent basis.

Repetitive, manual tasks are prime candidates here. Gemini Enterprise allows for the creation of custom agents that can automate these high-frequency workflows, freeing up employees to focus on higher-value activities. Examples might include:

• An IT help desk triaging incoming support tickets.
• A construction firm automating invoice capture, three-way matching, and approvals.
• An HR team streamlining new-hire onboarding.

High-Friction: Existing Process is Slow, Manual, or Multi-System

High friction use cases are ones that either don’t get run at all because they’re too cumbersome, or that create bottlenecks in larger processes that slow things down for the organization.

These sorts of workflows usually have extensive manual data entry. Multi-step approval chains. Cross-functional coordination (with the bottlenecks that inevitably come with it). Document-heavy processes requiring human approval.

Gemini Enterprise excels at automating data movement and/or automating certain decision cycles. Examples include:

• A hospital automating patient intake.
• A financial services firm accelerating regulatory reporting.
• A construction company streamlining change order management.

Scoring Use Cases

Note that often processes check multiple of these boxes. For example, patient intake is notoriously slow in healthcare settings, and demonstrates all three high-ROI traits. It takes up valuable time. It happens constantly. And it involves multiple data entry points and handoffs (insurance, payment, medical records, etc.)

As you identify potential use cases, we encourage you to rank them using these three criteria. A simple 1-10 rubric is usually fine, although some clients like to get more sophisticated and weight one of the variables. You might still choose a use case even if it doesn’t technically get the highest score, but we’ve found at a minimum this gives you an objective lens to evaluate potential opportunities.

But I Don’t Know What’s Possible…?

This is a common objection at this point, and a valid rebuttal to the “start with the problem” premise. The point isn’t to involve technologists at all, but rather to bring them in during this process. You can kick an initiative like this off with a presentation to business stakeholders on what Gemini Enterprise can do at a high level (if you’d like us to help facilitate one of these, feel free to reach out.) And you can use a “viability” check on the back-end once you’ve found high-potential opportunities. All you’re trying to avoid is having the technology dictate the solution.

How to Scope A Use Case

One you’ve found a viable Gemini Enterprise pilot, you need to scope it out. The below is a simple framework for doing so.

Step 1: Define the Problem

Clearly state the business problem you are trying to solve. What are the root causes of that problem? How does the process work current state?

For example: "Our private equity firm's portfolio monitoring process is slow and manual. It is delaying our ability to identify potential risks early enough to intervene."

Step 2: Identify Data Sources

Map out all the systems and data sources that are involved in the current workflow. What data is needed? Where does it currently live? How would a system access it?

Example: "We need to access financial data from our ERP (SAP), sales data from our CRM (Salesforce), and operational metrics from each portfolio company's proprietary systems."

Note that when you run into a situation where some of the data is difficult to access without significant custom engineering work, ask yourself whether you can execute on an 80% version without that data, or if it makes the pilot unusable. If the latter, you probably need to go back to the beginning and pick a different use case.

Step 3: Map the Workflow

Detail the step-by-step process of the current workflow. Who is involved? What are the handoffs? Where do bottlenecks exist?

For example, "The portfolio company's CFO emails a monthly performance report (Excel). An analyst manually enters the data into our master spreadsheet. The analyst cross-references the data with our CRM..."

It’s likely you won’t be able to automate everything about the process. But call out the steps that can be automated and the steps that need human intervention or review.

Step 4: Define the Measurable Outcome

Determine the key metrics that will define success. How will you measure the impact of the new workflow?

For example, "We will reduce the time spent on manual data aggregation by 80% and decrease the time to generate a portfolio performance report from 5 days to 1 day."

Keep in mind this is somewhat arbitrary. If it reduces time by 70% rather than 80, is it a failure? Probably not. But we still find creating a yardstick to measure success can be useful.

Pitfalls to Keep In Mind

As you go down this process, a few tips to avoid.

• Avoid High-Visibility Vanity Projects. Customer-facing chatbots are high-risk and often relatively low success. AI-generated marketing slop can create brand risk. When building internal credibility with these technologies, boring often wins. Think things like invoice processing, compliance documentation, IT ticket routing, onboarding processes for HR, etc.
• Fix your Process First. There’s a difference between “High-Friction” and “broken”. Don’t try to automate an already broken workflow.
• Think integration, not standalone tools. If it doesn’t stitch into your existing stuff it’s likely not high-value. Take advantage of Gemini Enterprise’s 100+ systems it stitches into. And as much as possible, surface insights inside of the tools they already use.
• Create clear lines of accountability. Committees rarely get projects over the finish line. One person ideally owns the outcome, has budget authority, and has success/failure tied to their performance review. This person should be close enough to operations to understand the workflows (or willing to get into the weeds to get there).
• Deploy in shadow mode first. Run it alongside humans, and review the outputs. This helps you build trust and identify edge cases. The
• Partner with specialists. A biased take, admittedly. But ****according to MIT, vendor-led implementations had a 67% success rate. For your first pilots at a minimum lean on their expertise. They can often teach your team to fish in the context of these engagements.

Define your first Gemini Enterprise workflow.

High-ROI Gemini Enterprise deployments aren’t the result of experimentation for its own sake. They come from choosing the right problems, grounding each in real operational needs, and designing workflows that make sense for the technology. By identifying high-context, high-frequency, high-friction opportunities and scoping them with intention, you can maximize your chances of delivering meaningful, measurable impact.

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