You don't need a complex model to know whether AI is worth it. Four numbers get you most of the way there.
Before investing in AI, most owners want a straight answer: will this pay for itself? A useful first estimate needs only a few numbers.
- Hours the task takes each week
- How much of that time AI can reduce
- How much of the team will actually use it
- Hours of human review it adds
- Loaded cost per hour and monthly running costs
A worked example
Take a 20-hour-a-week task at $40 an hour. With a 50% time reduction and 80% adoption, it frees 8 hours. Added review takes 3 hours back, leaving 5 net hours, or $10,400 a year. Subtract $2,400 in running costs and the workflow nets $8,000 a year.
Be conservative
Use the low end of your time-savings estimate, and count only the tasks you are confident AI can handle with human review. Treat freed time as capacity, not cash, unless it removes overtime, a planned hire, or outside spend. If the conservative number still works, you have a strong case.
In the AI Strategy Blueprint we build this model for your top five use cases with your real numbers.
See the Blueprint