AI ROI Calculator for Small Business
A useful automation must save net time after human review, and the software bill must fit that benefit. Run a hypothetical business case using your own numbers. No account, personal information or AI API is required.
What adoption and review time would break even?
Even a successful demonstration may fail financially once software and checking time are included. This tool also calculates the minimum percentage of weekly tasks that must adopt the assisted process to cover modeled monthly expenses, and the maximum human-review time per participating task allowed before the modeled value becomes negative at your current adoption. Both are sensitivity calculations based on your inputs, not market benchmarks or a prediction that a team will actually adopt a system. An impossible threshold is labeled unavailable rather than displayed as a misleading percentage.
How the calculation works
Monthly participating tasks = weekly task count × 52 ÷ 12 × estimated eligible-adoption share. Net saved minutes = original manual duration minus assisted duration and human-review duration. Multiply net hours by your loaded labor cost. Subtract software and other recurring charges plus a display-only allocation of one-time setup over the months selected. When monthly modeled cost is zero, ROI is shown as undefined rather than an invented percentage. Annualized net value is not a cash-flow forecast.
In the prefilled fictional example, 20 weekly tasks and 75% adoption correspond to 65 tasks monthly. A 30-minute process becomes 12 minutes plus 5 minutes checking: 13 minutes net saved per task, approximately 14.08 hours per month. At a hypothetical $30 labor cost, that is $422.50 in valued staff time. After $50 recurring costs and $20 per-month setup allocation, the modeled net is $352.50. Recovered staff hours are not automatically cash in your bank account.
Read our small-business AI ROI guide for realistic pilot design, sensitivity checks and why marketing promises of guaranteed earnings are not evidence. The NIST AI Risk Management Framework is a voluntary starting point for evaluating AI risks, rather than treating an arithmetic output as approval of a system.