AI access request automation delivers immediate ROI by reducing the time required to process permissions and provision tools. When processing 100 tasks per month, the net value reaches $3,875 after accounting for license and usage costs, assuming a loaded staff cost of $75 per hour.
The primary value driver is a 58-hour monthly reduction in manual effort. By lowering the time per task from 60 minutes to 25 minutes, organizations can redirect over a week of labor capacity toward higher-value operations.
Workflow ROI worked example
Worked example for AI Access Request 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 net value calculated?
Net value represents the labor value of time saved minus the total cost of the AI solution. In this workflow, saving 35 minutes per task across 100 monthly requests creates $4,375 in labor value. After subtracting the $500 monthly AI cost (covering licenses and usage), the resulting current net value is $3,875.
What does the payback period indicate?
The payback period shows how quickly the realized net value covers the AI costs. For AI access requests, a three-day payback indicates that efficiency gains outweigh the monthly expenditure almost immediately. This rapid return makes the workflow a strong candidate for the 'Expand' or 'Continue' decision states in a value management framework.
To move beyond estimates, NetLift measures verified time blocks to assign an Evidence Quality grade to your ROI. By comparing actual work duration against objective baselines, you can determine if a workflow spend is truly paying back. This deterministic model focuses on work outcomes rather than employee surveillance, ensuring data is used for value management rather than monitoring.