How NetLift Calculates AI Value

By Paige Gilmore, Founder, NetLift · Published 2026-07-28 · Updated 2026-08-07

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.

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.

How is labor value determined?

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.

What costs are included in the net value?

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.

How does NetLift handle future projections?

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.

What is Evidence Quality?

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.

Is this a surveillance tool?

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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