AI CONSULTING & AUTOMATION / A PRACTICAL ANSWER
How do you define success for an AI pilot?
The short answer
Define AI pilot success before examining the tool's best output. The standard should reflect the task, the effort around it and the consequences of mistakes. A faster draft is not necessarily a better workflow if preparation, checking and correction consume the benefit or the result is not dependable enough to use.
What to establish
Create representative examples and clear acceptance criteria with the people responsible for the work. Include awkward, incomplete and out-of-scope inputs. Record the existing method so the comparison does not depend entirely on memory or a vendor demonstration.
How to assess readiness
Assess preparation, review, corrections, exceptions and operating requirements alongside output quality. Decide which failures are unacceptable and when a person must intervene. Report the sample's limits and any unresolved questions instead of presenting a small test as a universal accuracy claim.
ILLUSTRATIVE EXAMPLE / NOT A CLIENT RESULT
Make it concrete.
For an internal document-summary pilot, the evaluator might check missing decisions, unsupported statements and review time. A fluent paragraph alone is not a sufficient pass condition if it omits the action the team needed to capture.
Before you commission
- Agree criteria and a current-process baseline.
- Use representative and difficult examples.
- Evaluate total effort and consequential failures.
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Further reading
FROM THE QUESTION TO THE WORK
A useful next step.
Bring the decision, the existing situation and the information you have. We can help define a scope before you commit to a wider project.
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