AI use case screening template: converge to your first real AI use case in one week

Many teams aren't stuck because they don't know what AI can do. They're stuck because they know too much.

I walked into a manufacturing customer's conference room last quarter. Seventeen sticky notes covered the whiteboard. Each one was an idea: customer service automation, quote parsing, yield forecasting, automated sales decks, contract review, internal knowledge base Q&A. The executives argued for three months without reaching agreement. In the end, nothing shipped. They had plenty of ideas. What they needed was a way to pick one.

Here's the tool: an AI use case screening template that narrows a pile of ideas down to your first real AI use case in one week, using three axes: value, feasibility, and data readiness. You can download the template below.

Why these three axes, not just ROI

An AI use case screening template is a decision tool that scores candidate use cases on three axes, business value, technical feasibility, and data readiness, to identify which one to deploy first.

We made mistakes early on. We looked only at value. Whoever saved the most money or whoever the boss wanted most, that's who we picked. And we'd end up choosing high-value ideas with garbage data and tangled processes. Six months later the demo looked beautiful, but actual usage measured in single digits. High value doesn't equal shippable.

Looking only at feasibility backfires just as badly. Engineers gravitate toward the technically elegant problem, then build something nobody actually wants. A slick toy sitting unused.

The third axis, data readiness, is the one most screening templates skip. It's often the most critical. For a RAG knowledge system, 80 percent of success depends on whether your documents are structured, properly tagged with access permissions, and kept current. If the data isn't there, even the strongest model just idles. This axis makes or breaks the project.

How to score the three axes

Score each candidate use case 1 to 5 on each axis. Establish anchors first, no guessing:

Multiply the three scores together instead of adding them. If any axis is zero, the total collapses, which is the point. A use case with 5 for value, 5 for feasibility, but 1 for data readiness multiplies to 25. A use case with consistent 4s across all three multiplies to 64 and wins instead. Your first use case should be the one with no weak links.

The one-week rhythm

Screening shouldn't take a month of meetings. Run through it in five days.

Start by listing every idea without filtering or critique. Aim for a dozen to twenty. Next, interview the people who'll actually use the system, not the executives but the daily practitioners. When someone says, 'I'm pulling this in Excel by hand, two hours a day,' listen. That beats ten PowerPoint slides. Then score all three axes, multiply the results, and rank them. Finally, write one page for your top candidate describing how it works in practice, who uses it, and how you'll measure adoption. If you can't write it clearly, move to the next option.

That one page is the real output. Not the score. It's a commitment you can measure against.

Convergence is just the beginning

A screening template gives you an answer, but it won't ship the product. Many teams nail the screening and pick the right use case, then fall apart during implementation because selecting a problem and delivering a solution are different things.

That's why we do FDE (front-line deployment engineering): engineers embed at customer sites, starting with that first use case from the screening template, and carry it through until real people use it daily. The demo doesn't matter. The screening score doesn't matter. What counts is actual adoption. Download the template and run through the screening yourself for a week.