How to estimate the return on an AI workflow pilot

Start with work that your team can count. Choose a recent period and measure how long people spend on a complete case, including finding information and correcting errors. Use comparable cases when you measure the pilot. Otherwise a change in volume or the mix of easy and hard work can look like an improvement.

Calculate the time that stays saved

Suppose a team handles 300 forms a month at eight minutes each. That is 40 hours of current work. In an illustrative pilot, 240 straightforward forms need two minutes of review each. The remaining 60 still require the full eight minutes. The new workload is 16 hours. If maintaining the workflow takes another two hours, 22 hours are available for other work each month.

At a hypothetical loaded labor cost of $35 an hour, that capacity is worth $770. If recurring software and management cost $450, the modeled monthly difference is $320 before setup costs. A $1,600 setup cost would take five months to recover under those assumptions. That calculation becomes cash savings only when staffing, contractor costs or overtime actually change. If people simply gain time, give that time a named use such as processing a backlog.

Test the assumption that matters most

Rerun the example with a higher share of exceptions. If 150 forms take eight minutes each and 150 take two, total handling time increases to 25 hours. With the same two hours of maintenance, 13 hours remain available. At the assumed hourly rate, the modeled value barely covers the recurring cost.

Use the pilot to measure the uncertain inputs. Have one owner count exceptions and another record review time. Production volume, actual fees and the cost of correcting costly mistakes belong in the final decision alongside the arithmetic.

Put this into practice

Bring a sample of the work and the tools your team uses. We can help define a first project, who reviews it, and how to tell if it works.

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