Guide
How to measure the ROI of AI automation
By Shreekant Pratap Singh, Founder, Technosys IT Management · Updated · 6 min read
Short answer
Measure the time a task takes and how often it happens before you automate, then measure again after launch. Annual saving equals hours saved per week, times loaded hourly cost, times 52, plus any revenue effects such as faster response or fewer errors. Subtract the build cost and yearly running costs. Report it monthly so the number stays honest.
Key takeaways
- Without a baseline measured before launch, ROI is a guess.
- Count running costs: platform fees, AI model usage and support.
- Include quality and speed effects, but keep them separate from hard savings.
- Track tasks handled without a person and exception rates every month.
The formula
Annual hard saving = hours saved per week × loaded hourly cost × 52.
Annual net benefit = annual hard saving + measured revenue effects − yearly running costs.
Payback period in months = build cost ÷ (annual net benefit ÷ 12).
| Illustrative input | Value |
|---|---|
| Hours spent per week today | 40 |
| Share of that work automated | 60 percent (24 hours) |
| Loaded hourly cost | $30 |
| Annual hard saving | 24 × $30 × 52 = $37,440 |
| Yearly running costs | $6,000 |
| Build cost | $15,000 |
| Payback | $15,000 ÷ ($31,440 ÷ 12) ≈ 5.7 months |
Getting a baseline you can trust
Time a sample of real tasks, not estimates from memory. Count volume from your systems: tickets, invoices, enquiries per week. Note the error or rework rate today, because automation often improves it and that is part of the return.
What to report after launch
Report hours saved, tasks completed without a person, exceptions routed to people, and any change in response time or error rate. Technosys reports these weekly on every automation engagement, so the return is visible rather than assumed.
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