Monthly review cost is calculated by multiplying the total AI outputs per month by the minutes spent reviewing each output, then multiplying by the reviewer's hourly labor rate.
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Results (computed from your inputs)
Review hours / month
33.3 hrs
Review cost / month
$2,500
Cost per output
$5.00
Review cost / year
$30,000
Estimate only. Track real evidence in NetLift.
To calculate your monthly human review cost, multiply your total monthly AI outputs by the minutes spent reviewing each one. Divide that number by 60 to find total hours, then multiply by the loaded hourly cost of the reviewer.
This calculation is a critical component of the NetLift value model. It ensures that the labor value of time saved is not quietly erased by the overhead of checking AI-generated work for accuracy or safety.
Monthly review cost = outputs per month x review minutes ÷ 60 x reviewer hourly cost.
Every result is computed in your browser from the numbers you enter — nothing is estimated for you. The same formulas run inside NetLift on verified tracked work, where results carry an Evidence Quality grade.
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In the NetLift methodology, current net value is defined as the labour value of realised time saved minus the full AI cost. This cost includes more than just licenses; it accounts for implementation, training, and the ongoing expense of human review and rework. If the review time is too high, the net value may indicate a 'Review' or 'Stop' decision state for that specific workflow.
Payback is the time required for net value to cover the total AI cost to date. Every minute spent in a 'Multi-Agent Adversarial Review Workflow' or manual check increases the time it takes to reach a positive return. By tracking these minutes as verified work, you can move from an 'Estimate Only' to a 'Verified' Evidence Quality grade, providing a finance-credible view of AI performance.
NetLift measures the actual work and value produced, rather than individual productivity. By comparing the time the work would take without AI against the time taken with AI (including review), NetLift determines whether a workflow should be expanded or improved. This is done without employee surveillance, such as keystroke logging or screen monitoring, focusing instead on objective labor value and evidence quality.
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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.
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