Is the process understood?
If people cannot agree on the current steps, owner, inputs, and correct output, map the process before adding AI.
Process before tool
Choose one AI use case you can understand and control.
A useful first experiment starts with a real task, an accountable owner, approved information, a review point, and a safe fallback—not with a tool looking for a problem.
First-use decision framework
Five questions before testing anything.
Can the first test use low-risk information?
Start with public, synthetic, or specifically approved information. Do not begin with protected or confidential records.
Can a person review the result before it matters?
A suitable first use has a named reviewer who can detect errors and prevent an unsafe action or commitment.
Can usefulness be observed?
Choose a baseline such as time spent, rework, completeness, or error types, then compare the narrow test against it.
Can the team stop safely?
Keep the existing process available until the new use is understood, approved, and maintainable.
Potential first tests
Suitable when narrow and reviewed.
- Drafting a first version from approved, non-sensitive source material for a person to review.
- Classifying synthetic or approved low-risk examples to test a repeatable decision rule.
- Turning a defined internal checklist into prompts that help a person notice missing information.
- Summarizing public material when the reviewer can check the source and correct the output.
Do not start here
Unsuitable without stronger controls.
- Making hiring, safety, credit, legal, medical, or other consequential decisions without qualified human review.
- Uploading customer lists, employee records, financial account data, credentials, health information, or confidential client material to an unapproved tool.
- Automating a process whose owner, inputs, correct output, and exceptions are still disputed.
- Letting generated content make a commitment, send a consequential message, or change a system without an accountable review point.
A narrow test-and-measure sequence
Keep the experiment small enough to stop.
- Observe the current task and record a simple baseline: time, rework, missing information, or common error types.
- Remove unnecessary steps and define what a correct output must contain.
- Classify the information, choose approved test material, and name what must never enter the tool.
- Give one person responsibility for reviewing every output in the test.
- Run a small sample, record corrections and exceptions, and compare it with the baseline.
- Stop, adjust, or expand only after the owner understands the result, fallback, cost, and maintenance responsibility.
Common adoption failures
- Automating waste instead of simplifying the process first.
- Using a polished demonstration as evidence of reliable operation.
- Leaving review responsibility vague because the tool appears confident.
- Expanding before exceptions, data handling, and fallback are understood.
- Creating a workflow nobody is assigned to maintain.
Run Better NW can help frame a process, control, experiment, and adoption plan. It does not promise that AI is appropriate for a task, eliminate the owner’s judgment, or replace qualified advice in regulated or high-consequence work.
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