Calculator · 7 min + calculation
Calculate the ROI
of AI automation.
A transparent calculator to estimate freed capacity, recurring cost and payback time without treating every saved minute as a fictional cash saving.
Key takeaways.
- 01
A freed minute is available capacity first, not automatically a cost reduction.
- 02
A conservative scenario must include adoption, exceptions, human checks and operating costs.
- 03
Measure before the pilot, during four weeks and after stabilisation using the same method.
Test your scenario.
Change the assumptions. The calculation estimates a monthly value for freed capacity, subtracts recurring cost and compares the result with setup cost.
Decision-support tool excluding quality, risk, adoption and taxation. It does not guarantee commercial gains.
A deliberately clear formula.
Hours freed up = monthly volume × average duration × share actually automated. Gross value = hours freed up × fully loaded hourly cost. Monthly net value = gross value − recurring system cost.
Payback time divides initial cost by monthly net value. If that value is zero or negative, no timeframe is produced: the scope needs to change or the project must be justified by other measurable benefits.
DECISION POINTDo not present freed capacity as an accounting saving. It becomes valuable if it absorbs more volume, shortens lead times, avoids recruitment or enables more useful work.
Quality matters as much as speed.
Faster automation that increases rework or errors destroys value. Set a baseline before the pilot, then observe the same indicators.
- 01
Weekly volume processed and seasonality.
✓ - 02
Average active time, excluding waiting unrelated to the process.
✓ - 03
Exception rate requiring human intervention.
✓ - 04
Error rate and correction time.
✓ - 05
End-to-end time from input to output.
✓ - 06
Adoption rate among the people concerned.
✓ - 07
Variable costs: model calls, storage, monitoring and support.
✓
Scope a pilot that can reach a real conclusion.
Choose a workflow frequent enough to produce data but limited enough to correct quickly. Capture at least a conservative, expected and high scenario, varying automation and adoption rates rather than only volume.
At the end, decide to expand, correct or stop. A useful pilot may conclude that automation is not cost-effective: it will then have avoided a more expensive deployment.
Check and explore further.
We prioritise official texts and reference frameworks. This guide's recommendations are our practical interpretation of those sources, to adapt to your context.
- 01NIST — AI Risk Management Framework ↗
Measure risks and results within their usage context.
- 02Initial IA method — August 2026 version ↗
Decision-support formula designed to remain explainable and adjustable.