NetLift calculates AI value by subtracting the time taken to complete work with AI from a verified baseline, then deducting the total cost of ownership—including licenses, training, and rework—to determine net return.
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NetLift uses a deterministic model to track the actual impact of AI adoption on organizational work. By measuring the delta between work time with AI and established baselines, the platform provides a finance-credible view of realized labor value.
Calculations are based on the work performed rather than individual productivity. This approach ensures that capital allocation decisions are driven by net value and payback periods rather than sentiment or hype.
NetLift converts time saved into a monetary figure by multiplying the hours saved by the loaded hourly cost of the staff performing the work. A default assumption of $75 per hour is used unless a specific organizational rate is provided. This calculation focuses on the labor value of realized time savings, providing a concrete baseline for return on investment.
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To calculate current net value, NetLift deducts the full AI cost from the realized labor value. This cost includes more than just seat licenses; it accounts for usage fees, implementation expenses, and training time. Crucially, the model also subtracts the cost of human review and rework where tracked, ensuring that the 'hidden' labor of AI oversight is fully reflected in the final ROI.
Future value is always stated separately from realized value to maintain financial integrity. It is calculated by multiplying expected recurring time savings by expected volume. This distinction allows finance teams to see what has actually been saved to date versus what is projected to be saved if current performance levels hold.
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Every metric in NetLift is assigned an Evidence Quality grade, ranging from Estimate Only to Verified. This grading system weights data based on the strength of the baseline; objective historical or cohort data ranks higher than self-estimated savings. Factors like sample size, data recency, and cost completeness determine the grade, helping leaders understand the risk level of the reported numbers.
NetLift measures work and value, not individual activity. The methodology specifically excludes employee surveillance. There is no keystroke logging, no screen capturing, and no browser monitoring. The focus remains strictly on the economic output of AI-assisted tasks compared to non-assisted baselines.
NetLift enables organizations to decide whether AI spend pays back by categorizing every measured area into five decision states: Expand, Continue, Review, Improve, or Stop. By comparing realized time saved against the total cost to date, NetLift provides a clear payback period and an Evidence Quality grade to justify further investment or decommissioning.
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About the author
Paige Gilmore · Founder, NetLift
Paige Gilmore is the founder of NetLift, the AI Value Management platform that helps organisations measure the cost, savings and return of AI adoption.
Paige Gilmore on LinkedInAvoid double-counting AI value by strictly separating realised savings from future projections and subtracting the full cost of adoption, including rework and training, from gross labour value.
Read ai-roiAI quality is measured by the reduction in human review and rework time required to achieve a finished output. Higher quality models decrease the time spent on corrections, directly increasing the net value and shortening the payback period.
Read ai-roiAI rework is measured by tracking the human time spent reviewing and correcting AI-generated output, then multiplying those hours by the loaded staff cost. This total is subtracted from the gross labour value of time saved to determine the net value of an AI implementation.
Read ai-roiAI payback is the time required for the net labor value of realized time savings to cover the total investment cost, including licenses, implementation, and training. It is calculated by dividing the total cost to date by the monthly realized net value.
Read ai-roiHard savings are direct reductions in cash outflow, such as reduced headcount or software spend, while capacity value is the dollar-equivalent of time saved that allows existing staff to complete more work.
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