Find the AI work worth doing first
A practical workflow audit: separate touch time from delays, compare opportunities, and choose a first build with a clear owner and measurable value.
An AI workflow audit should tell you which work to improve first, what the improvement is worth, and what could prevent it from working. Its useful output is a ranked set of workflow briefs with evidence behind the order.
Start with one recurring process and the people who run it. Use the same method across departments when you need a wider transformation plan.
Capture actual work
Follow recent items from arrival to completion. Include routine work, exceptions, rework and a busy period. A small sample helps discover the process; it does not establish a reliable annual savings forecast.
For each step, record the input, system, operator, decision and recipient. Ask what information the person searches for, what makes them pause, and who handles a case when the usual owner is absent. Save representative examples with the access controls the information requires.
Include the receiving team. An output can look complete to its producer while creating extra checking for finance, support or delivery.
Separate staff time from waiting
Touch time is time a person actively spends on the item. Wait time is elapsed time before the next step starts. Record both; they support different improvement cases.
Consider this illustrative weekly process: 100 requests each need six minutes of preparation and four minutes of review. They also wait an average of two days for assignment. If a proposed workflow cuts preparation to two minutes and leaves review unchanged, the gross capacity opportunity is 400 minutes, or six hours and 40 minutes a week. Subtract additional maintenance and exception handling to estimate net capacity.
Reducing the two-day queue would improve turnaround. It would not create two days of employee savings per request. If waiting dominates, examine assignment rules and reviewer availability before buying a faster drafting tool.
Rank the evidence, then apply constraints
| Question | Evidence to collect |
|---|---|
| Is there enough recurring work? | Actual item counts and seasonal variation. |
| Can we improve it materially? | Touch time, avoidable rework and the observed bottleneck. |
| Can a system handle the inputs? | Representative formats, missing data and access requirements. |
| Can mistakes be found and corrected? | Review method, possible consequences and recovery steps. |
| Will anyone own the result? | A named operator, sponsor and maintenance owner. |
Rank candidates by expected benefit and effort using ranges where evidence is weak. Apply permission, risk and ownership constraints separately. A large theoretical saving should not compensate for having no lawful data access or no one able to review a consequential decision.
Leave a decision someone can act on
For the leading candidate, write down the boundary, baseline, proposed change, exceptions, dependencies, estimated cost and next test. Record why other candidates were deferred. This makes the selection inspectable and avoids restarting the same debate at the next meeting.
The next step is designing the revised workflow, then agreeing on a test with the operator. Our workflow optimization work follows that sequence. A completed audit should make it possible to reject an unsuitable build as confidently as approving a promising one.