AI Pilot Scorecard: Decide Whether a Team Trial Should Continue

An AI pilot scorecard shows whether a tool helps with one task after a person checks and fixes its work. Compare it with the way the team works now. Score the results and log each fault. Use that record to choose whether to extend, change or stop the trial.

This worksheet is for routine team work, such as turning approved notes into a weekly team update. We wrote the rubric and sample below to help plan a trial. They do not report LastVerified product tests or a proven benchmark. If you still need to choose an approach, read our build-versus-buy guide .

Define one task and its limits

Write one sentence that names the input, output and person who checks it. For example: “The tool drafts a weekly project update from the notes supplied. The team lead checks each fact before sharing it.” Keep sending, outside research and choices about people out of this trial.

Give the pilot a finish date and name who can stop it. Record the product and plan. Note the model version, active features and prompt version too. If the tool does not show its model version, say so in the log. A later change to one of these fields can mean you need to check the task again.

Before you upload files, ask the person who approves their use to resolve any open data questions. Our vendor data questionnaire helps you keep track of those answers. A good task score does not grant consent to use a set of files.

Write the scoring rules before the trial

Score five aspects of the task, using rules that a person can check. The 0–2 scale below gives the team a shared way to discuss a small trial. Each row matters for a different reason. Agree which faults pause the trial before anyone sees a draft they like.

Keep all five scores in view. A clean format cannot make up for a made-up due date. Define a “material fact” for this task: a change to the owner, date or project status would count in the sample above. Small style edits would not count as the same kind of fault.

NIST’s AI RMF Measure playbook calls for metrics that fit the task, clear limits on what counts as a pass, and a record of what was not measured. This worksheet draws on those ideas for a small team trial. It is not a NIST test or seal of approval.

Use the same cases for each option

Build a small set of cases. Include a clear update, notes with gaps, dates that clash, and a request outside the agreed task. Write what should happen beside each case. For dates that clash, the note might say “flag the conflict and ask the team lead.” Do not choose a date the source cannot prove.

Run the same cases through the team’s usual process first. Time how long a person takes to draft, check and fix an update that meets the task. Then try each tool with the same inputs and rules. Test prompt changes in a new round. This keeps the reason for each result clear.

Keep the first output and failed attempts. If someone keeps trying until a draft looks good, count each try and the time spent checking it. Track each claim back to its source. A polished final draft alone hides the work it took to reach it.

Ask the person who checks the draft to score it before the team shares its views. If two people disagree, use the source and the rubric to resolve the point. A small set of cases can show how a tool fails. It cannot prove how often it will fail in daily use.

Count review time and rework

Time the whole task, from getting the input ready to signing off the output. Count the prompt work and retries, as well as source checks, fixes and handoff. Keep one-time setup in its own row. That helps the team see how much work each later task needs.

Here is a worked example with made-up values. It is not a product test. A manual update takes 12 minutes. Getting the AI input ready and making a draft takes 3 minutes; checking and editing take 7 minutes. The saving is 12 − (3 + 7) = 2 minutes per update. A claim of a 9-minute saving would leave out the review.

If setup took 40 minutes, 20 such updates would recover that time at the sample 2-minute saving. This assumes the saving lasts. Tool fees and changed task needs belong in their own entries. If the tool makes the task slower, record that result too.

Separate stop conditions from the average

Write pause rules as events a person can spot. In this draft-only task, one would be a promise that was not in the notes. Another would be a source conflict stated as fact. Sending an unchecked draft would also pause the trial. Log what happened and keep the input and output.

Do not erase a fault because a retry works. Record the fix and test a similar case after you change the prompt or workflow. Name who gets each open issue and what happens if that person is away. A queue with no owner is not a complete handoff.

Distinguish tool faults from gaps in the process. Missing notes need an input fix. An unclear review role needs a named owner. Neither proves that a different model would solve the problem.

Record the decision and its limits

End with a short record of the choice. Include the task and case set, scores, review time, open faults and owner. Set the next check date. Choose “extend this trial,” “change and rerun these cases,” or “stop this workflow.” Give a reason someone else can check.

For example: “Keep draft-only updates for this team. Each tested fact had a source, but handoff failed when the team lead was away. Name a backup owner and rerun that case before wider use.” This is a sample choice, not our test result. A wider use needs its own evidence.