NUMBERS FIRST
This AI automation ROI calculator turns three numbers you already know into hours returned per year. Volume, minutes per task and how much of it is routine. Every assumption is visible, and the model deliberately leaves several things out.
Model your own numbers
Hours returned a year
2,184
Annual saving
USD 69,888
Share of the task an agent takes 70%
Three worked scenarios
| Scenario | People | Hours a week each | Hours returned a year | Annual saving |
|---|---|---|---|---|
| Small team | 2 | 8 | 582 | USD 18,637 |
| Medium team | 5 | 12 | 2,184 | USD 69,888 |
| Large team | 15 | 16 | 8,736 | USD 279,552 |
Show assumptions
Hours returned a year = people on the process, times hours a week each, times the share an agent takes, times 52 weeks.
Annual saving = hours returned a year, times the loaded hourly cost.
There is no hidden coefficient and no efficiency multiplier. The model does not account for the cost of running the agents, which is measured per task during the prototype and is agreed before any build starts.
These are shapes, not promises. Your numbers come out of the readiness audit.
What the AI automation ROI calculator actually calculates
The formula is one line, and it is on the page rather than behind a form:
Multiply that by your own loaded hourly cost and you have the annual figure. We never supply the hourly cost, because the honest number includes employment costs, tooling and management overhead that only your finance team knows.
Two assumptions sit behind the arithmetic and both are stated where you can argue with them. First, an agent handles the routine share only, and the rest still reaches a person. Second, hours returned are hours moved to other work, not hours removed from a payroll. Which of those it becomes is your decision, not the model’s.
What the shape looks like
Support ticket triage
Inputs: 4,000 tickets a month, 6 minutes each, 70% routine. Modeled result: 3,360 hours returned per year. See the agent that does this: Ticket Triage Agent
Invoice matching
Inputs: 2,500 invoices a month, 9 minutes each, 80% routine. Modeled result: 3,600 hours returned per year. See the agent that does this: Invoice Matching Agent
Lead research and enrichment
Inputs: 900 leads a month, 14 minutes each, 65% routine. Modeled result: 1,638 hours returned per year. The whole process, not the step: business process automation
HONESTLY
What is missing from this number
A model that counted only the upside would produce a bigger number and a worse decision. If the case still works after these five, it is a case worth taking to the audit.
Integration effort
Reaching your systems is real engineering, and it is the largest single variable in a build.
Review time during rollout
Shadow and assisted modes need a person comparing outputs for a few weeks. Those hours are a genuine cost and they are not in the figure above.
Change management
Telling a team their work is changing, and keeping them, is not free.
Model and compute spend
Billed to you by your providers at cost. Small next to the hours, never zero.
The exceptions that get harder
Once the routine share is automated, what is left is the difficult residue, and it takes longer per item than the average you typed.
Send me this model
Send me this model
We send the calculation, your inputs and every assumption behind them. Nothing else.