AI test generation reduces the time required for testing tasks from 60 minutes to 25 minutes. Based on a loaded staff cost of $75 per hour and 100 tasks per month, this workflow saves 58 hours of engineering time, creating a monthly labor value of $4,375.
After subtracting $500 for monthly licenses and usage, the current net value stands at $3,875 per month. These figures represent realized savings that allow engineering leaders to shift resources from manual scripting to higher-value development.
Workflow ROI worked example
Worked example for AI Test Generation ROI using stated NetLift assumptions (replace every input with your own tracked data):
| Input (stated assumption) |
Value |
| Tasks per month |
100 |
| Time without AI (per task) |
60 min |
| Time with AI (per task) |
25 min |
| Loaded staff cost |
$75/hour |
| AI cost per month (licences + usage) |
$500 |
| Computed result |
Value |
| Hours saved per month |
58 h |
| Labour value of time saved |
$4,375 / month |
| Current net value |
$3,875 / month |
| Payback |
about 3 days |
Every input above is an assumption until you track real work. In NetLift the same calculation runs on verified time blocks, so the result carries an Evidence Quality grade instead of being an estimate.
How is the payback period calculated?
Payback is determined by how long it takes for the net value of time saved to cover the total AI investment. With a monthly cost of $500 and a high volume of time saved, the investment typically pays for itself within three working days. This calculation uses a deterministic model that subtracts the full cost of licenses and usage from the realized labor value.
What determines the decision to expand AI testing?
Every measured workflow is assigned a decision state such as Expand, Continue, or Review. If the net value remains high and the Evidence Quality grade is high—meaning the data is based on verified time blocks rather than estimates—the workflow is a candidate for expansion. This ensures that budget is allocated based on financial performance rather than hype.
NetLift measures the actual time saved per task against objective baselines to determine whether an AI investment is delivering a return. By calculating the delta between manual work and AI-assisted output, it assigns an Evidence Quality grade to the $3,875 net value, ensuring the numbers are audit-ready and free from the inaccuracies of self-estimation.