AI & Machine Learning
AI Automation Cost and ROI Calculator
Add up everything an AI workflow really costs each month, not just the tokens, and see whether the time it saves pays for it.
Free to useNo sign-up requiredNo watermarkRuns in your browser
Last reviewed: 30 September 2026 by Vishal Senthilkumar
The token bill is often the smallest line in an AI automation. A workflow that reads an email, looks something up, drafts a reply and logs it also pays for other APIs, the platform it runs on, and - usually the largest item - the people who check its work.
This calculator puts all of those on one monthly bill, divides it by the runs that actually succeed, and, if you enter how long the task takes by hand, compares it with the value of the time saved.
How this tool works
Enter the volume
Runs per day, working days per month and how many model calls each run makes.
Enter the AI usage and prices
Average input and output tokens per call, and prices per 1M tokens.
Add the other costs
Per-run API fees, fixed subscriptions, and the platform or hosting cost.
Add human review and success rate
What share of runs a person checks, for how long, at what hourly cost - and how many runs succeed.
Optionally, add the ROI inputs
Minutes a person would spend on the task, and what that time is worth.
How it works
Runs per month are runs per day times working days. The AI cost of one run is the number of model calls times the cost of one call (input tokens × input price + output tokens × output price, per million tokens).
Other API and tool costs have two parts, kept separate on purpose: a cost per run for pay-as-you-go services, and a fixed monthly amount for subscriptions that do not change with volume. The platform cost is a flat monthly figure.
Human review is runs × share reviewed × minutes per review ÷ 60 × hourly cost. Total monthly cost is the sum of all four; cost per run divides it by all runs, and cost per successful task divides it only by the runs that succeed, since failed runs deliver nothing.
The optional ROI section values the time saved on successful runs only - a failed run still has to be done by hand - and compares it with the total cost. ROI is the net benefit divided by the total cost.
Common use cases
- Pricing an AI agent or workflow before building it, to see whether the numbers work.
- Comparing a cheaper model that needs more review with a better one that needs less.
- Explaining to a manager or client what an automation costs per task, all-in.
- Finding which cost line to attack first - usually review time, not tokens.
- Checking how ROI changes as the success rate improves.
Why cost per successful task is the number to watch
Cost per run flatters a workflow that often fails. If one run in five has to be redone by hand, you pay for the failed run and for the person who fixes it. Dividing by successful runs only shows what each useful result really costs.
It also makes trade-offs visible. A more capable model can cost several times more per call yet lower the cost per successful task, if it raises the success rate enough to cut review and rework. Try both sets of numbers.
Costs this calculator does not include
- Building and maintaining the automation - developer time, prompt changes, monitoring.
- Retries and long-tail runs that use far more tokens than average.
- The cost of errors that slip through review.
- Taxes, currency conversion and committed-use discounts.
Formula
AI cost per run
calls × (input tokens × input price + output tokens × output price) ÷ 1,000,000
Human review
runs × review % × minutes ÷ 60 × hourly cost
Cost per successful task
total monthly cost ÷ (runs × success rate)
Value of time saved
successful runs × minutes saved ÷ 60 × hourly value
ROI
(value of time saved − total cost) ÷ total cost
Worked examples
An email triage agent
200 runs a day for 22 days is 4,400 runs. Three calls of 2,000 input and 500 output tokens at $3/$15 per 1M cost $0.0405 a run - $178.20 a month. Add $8.80 in per-run API fees, $50 for the platform and $880 for reviewing 10% of runs for 3 minutes at $40/hour: $1,117 a month, $0.25 per run and $0.27 per successful task at 95% success. Saving 10 minutes on each of 4,180 successful runs is worth $27,866.67.
A small, unreviewed workflow
100 runs a day for 20 days, one call of 1,000 in and 1,000 out at $1/$4: $10 of AI. With $0.01 per run in tool fees, a $30 subscription and a $100 platform, the total is $160 - $0.08 per run, or $0.10 per successful task at 80% success. Saving 2 minutes per success at $30/hour is worth $1,600, a net $1,440 and an ROI of 900%.
Frequently asked questions
How many AI calls does a typical automation make?
Simple workflows make one call per run. Agents that plan, use tools and check their own work commonly make several, and each call re-sends the growing context, so later calls tend to have more input tokens than the first.
Should human review be included?
If anyone checks the output, yes. Review time is frequently the largest cost of an AI automation, and leaving it out makes almost any workflow look cheap. Reducing it - by reviewing a risk-based sample rather than everything - is often the biggest saving available.
Why is the ROI based on successful runs only?
Because a failed run does not save any time: somebody still has to do the task by hand. Counting failed runs as savings would overstate the benefit.
What hourly cost should I use?
Use the fully loaded cost of the person’s time - salary plus employer taxes, benefits and overheads - not just the hourly wage. For the ROI, use the value of the time to your business, which may be the same figure.
Can I leave out the ROI?
Yes. Clear either ROI field and the calculator shows costs only.