The easiest way to fake AI ROI is to count every minute theoretically saved and ignore everything annoying that happens around the workflow. Real ROI comes from net improvement after review time, setup time, tool cost, and adoption friction.
Start with the current workflow
If you do not know how the work is handled today, you cannot estimate improvement honestly. Measure the current time, error rate, handoff friction, and how often the task actually occurs.
Add the hidden costs back in
- human review time
- prompting and retry overhead
- setup and maintenance effort
- time lost if the team stops trusting the output
Look for robustness, not best-case outcomes
If the workflow only produces a great ROI under perfect assumptions, it is weak. Strong AI ROI usually comes from boring repeated work where the gains survive normal variance.