Evidence-first authority page
How to Calculate ROI on AI Automation
A practical framework for estimating AI automation ROI honestly, including the costs that are commonly left out of vendor calculators.
Direct answer
Calculate AI automation ROI by comparing the fully-loaded cost of automation (subscription, integration time, ongoing maintenance, and error-correction overhead) against the actual time saved at your real usage volume — not the vendor's example scenario — since vendor-provided ROI calculators typically omit integration and maintenance cost entirely.
Last reviewed 2026-08-29
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Costs vendor calculators typically omit
- Integration engineering time, which is rarely zero even for a 'no-code' tool once real edge cases appear.
- Ongoing maintenance as the underlying systems (APIs, data formats) change over time.
- Error-correction overhead — time spent catching and fixing the automation's mistakes, which offsets some of the time saved.
A simple honest framework
Estimate: (time saved per task × actual task volume per month) − (subscription cost + amortized integration time + estimated error-correction time). Run this at your real, current usage volume, not a vendor's example scenario, and revisit it after a few months of real operation rather than trusting the pre-launch estimate indefinitely.