Speed up procurement. Keep control of the order.

In this worked case, the pilot measures order preparation. Human approval is required before submission. The evidence says nothing yet about how much time the approver spends checking the AI output or correcting exceptions.

Start your closing answer with the supported scope:

“I recommend expanding the drafting trial to representative order types while keeping human approval before submission. Preparation is 18% faster, but the business case depends on the time saved after checking and corrections. I would approve a broader rollout only if the complete workflow improves and the order controls continue to work.”

The phrase “representative order types” needs substance. If the pilot covered repeat purchases from approved suppliers, include the common exceptions that consume staff time: changed quantities, an unfamiliar delivery address, incomplete specifications, and a price that differs from the agreed terms. The trial should reveal how the workflow handles these situations.

Keep approval in the actual system. A request for the model to seek permission is weaker than a workflow in which the tool cannot submit an order until an authorised approver releases it.

Suppose the interviewer supplies these illustrative timings:

Preparation saves 3.6 minutes, which is 18% of 20. Approval adds three minutes. The complete process saves 0.6 minutes per order, or 2.5% of the original 24 minutes.

At 6,000 orders a year, that is 60 hours saved. Quoting 360 hours would count the drafting benefit and ignore the extra review work.

Now suppose the tool needs 40 hours of annual administration, training and support. The net capacity released is 20 hours. A licence fee, implementation cost or substantial remaining error burden could easily outweigh that benefit.

Do not call those 20 hours a cash saving unless the company can reduce a cash expense. If the team uses the time to clear a backlog, explain the value as extra capacity and show what it will accomplish.

A weak response to the disappointing calculation is to remove the reviewer. That would discard a required control to rescue the savings forecast.

Instead, inspect what the reviewer is doing. Are they correcting wrong quantities? Searching for the source of the quoted price? Re-entering information because the draft does not fit the purchasing system? Each problem suggests a different improvement.

For example, a draft that links each price to the approved catalogue may reduce verification time. A better template may eliminate re-entry. Restricting the tool to repeat orders may improve consistency while leaving unusual purchases with the existing process.

Then rerun the complete calculation. If checking returns to four minutes, the tool saves the full 3.6 minutes per order. Across 6,000 orders, 360 hours less 40 support hours leaves 320 hours of capacity. That is a materially different case, achieved while preserving approval.

The next step should target the source of review effort. “Train staff and monitor performance” leaves the actual problem untouched.

Ask the procurement owner to define the minimum worthwhile benefit before expanding. The test needs three types of evidence:

• Work completed: staff time from starting the order through approval, including correction and exception handling.
• Order quality: whether the approved order contains the right items, quantities, prices and delivery details, with failures traced to the relevant step.
• Operating cost: licences, support, training and integration costs for the proposed scope.

Elapsed turnaround time also matters if requests wait in an approval queue. A tool can reduce staff minutes without making an order arrive sooner. Keep those measures separate so the client can see what improves.

The procurement owner should review the results with the people who prepare and approve orders. Expand the drafting workflow where the net benefit clears the client's requirement. Revise or stop the parts that add work without sufficient value.

If the interviewer asks, “Wouldn't automatic submission unlock much bigger savings?”, acknowledge the potential and keep the evidence straight:

“It could remove some approval effort, but it would change the control model and the consequences of an error. The current trial has not tested that decision. I would first prove the value of assisted drafting and treat any change to submission authority as a separate proposal.”

That answer does not require a speech about every possible AI risk. It identifies the exact leap in the argument.

Try your own closing answer using the 24-minute and 23.4-minute totals. State the scope, the net result and the next improvement you would test. Then use Cybersecurity Product Expansion in the final-synthesis library to practise making another recommendation where attractive benefits sit beside an unresolved condition.