AI CONSULTING & AUTOMATION / A PRACTICAL ANSWER
What should an AI workflow audit examine?
The short answer
An AI workflow audit should examine a specific piece of work, its inputs, decisions, outputs and failure consequences before proposing technology. For a small business, this can be an opportunity review rather than a financial or compliance audit. Define that boundary so the engagement does not imply assurance it cannot provide.
What to establish
Map the current steps and the people who understand them. Identify repeated effort, inconsistent inputs, judgement calls and the systems involved. Establish how a good result is recognised and where errors require intervention. Include tasks a simpler process change could improve without AI.
How to assess readiness
Produce a prioritised set of candidates with evidence, dependencies and evaluation needs. Distinguish a feasible pilot from a production commitment. The audit should help the business choose a next step or reject an unsuitable idea, rather than automatically recommend automation everywhere.
ILLUSTRATIVE EXAMPLE / NOT A CLIENT RESULT
Make it concrete.
A team preparing repetitive internal summaries might have a testable task. The same team giving consequential advice to customers may need very different controls and specialist review. Calling both an easy automation opportunity would hide the important distinction.
Before you commission
- Bound the task and meaning of the audit.
- Map inputs, judgement and failure consequences.
- Recommend a specific next test with ownership.
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Further reading
FROM THE QUESTION TO THE WORK
A useful next step.
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