How should a plant measure the success of an AI pilot?
Compare a defined task with the existing process, including the quality of results, review effort, errors and user experience.
What to consider
Before the pilot, agree on representative test cases, a baseline and the outcome needed to continue. A faster answer is not useful if it is wrong, difficult to verify or requires more correction time. Include frontline users and the owners of the information in the review.
Practical steps
- Define the user, task, source set and test questions before measuring.
- Record current task time and the quality of results using the normal process.
- Track useful results, unsupported answers, review time and relevant access issues.
- Decide in advance who reviews results and what conditions would pause or stop the pilot.
A practical example
A team tests an AI document search tool on a representative sample of maintenance questions. It compares time to find the correct approved source with the existing method, while tracking incorrect answers, inaccessible sources and review effort. The owner agrees on success criteria before testing and reviews results with the users. Faster responses alone do not establish success if people cannot verify the correct document.
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See how KANE approaches this work and what an engagement includes.
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