Measure the handoff, not only the activity
A task can become faster while the overall process stays slow. An order may enter NetSuite quickly and still wait for a corrected address. A report may generate instantly and still require an analyst to reconcile definitions.
An illustrative review follows an order from acceptance to a usable invoice. Record where it waits, where information is re-entered and which exceptions need investigation. That helps identify whether the useful change belongs in the screen, the data or the handoff.
The measure should follow that whole journey. Saving entry time is useful, but only part of the result if another team inherits more corrections.
Give AI a task small enough to judge
A broad ambition to “use AI” is difficult to evaluate. A defined task gives the team something to test: the input, the expected output, the permitted action and the review required. The narrower starting point makes errors and benefits easier to observe.
Build an evaluation set with routine cases, incomplete information and a meaningful exception. Decide in advance what the capability should do when it cannot produce a dependable answer. Compare the effort of the full workflow, including review and corrections, with the baseline.
Keep the boundary between a suggestion and a consequential action explicit. A useful design explains what a person approves, what is logged and how the team can pause the workflow. Expand the scope only when evidence supports it.
Every customization should have a reason and an owner
A customization can preserve an important business requirement. It can also outlive the problem it originally solved. Periodically ask who uses it, what would fail without it and whether a supported capability now addresses the same need.
Keep a short record of the purpose, dependent processes, maintenance owner and representative test. When a release changes the surrounding platform, that record helps the team assess impact without rediscovering the entire design.
Before adding another field, workflow or script, consider the ongoing work it creates. Someone must keep its meaning clear, maintain its permissions and test it when related processes change. Make that responsibility part of the decision.