A procurement research agent delivers a current net value of $4,458 per month by saving 108 hours of staff time. Each successful outcome costs $2.31 after accounting for platform fees and human review.
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A procurement research agent yields a current net value of $4,458 per month. This return is calculated by subtracting the platform cost and human review time from the total labor value of the 108 hours saved.
At a $1,500 monthly platform cost, the cost per successful outcome is $2.31. This figure is based on a 65% success rate for 1,000 monthly interactions, factoring in the time required for staff to handle escalations and verify outputs.
Worked example for Procurement Research Agent using stated NetLift assumptions:
| Input (stated assumption) | Value |
|---|---|
| Interactions handled per month | 1,000 |
| Accepted / successful outcomes | 65% |
| Escalated to a person | 35% |
| Staff minutes saved per accepted outcome | 12 min |
| Human review per accepted outcome | 2 min |
| Loaded staff cost | $55/hour |
| Agent platform cost per month | $1,500 (stated assumption) |
| Computed result | Value |
|---|---|
| Successful outcomes per month | 650 |
| Cost per successful outcome | $2.31 |
| Net staff time saved | 108 h / month |
| Labour value of time saved | $5,958 / month |
| Current net value | $4,458 / month |
Escalation, review and rework are part of the true cost of an AI agent. Track them — an agent that resolves fewer tickets with less rework can beat one that closes more tickets badly.
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Efficiency is measured by the ratio of accepted outcomes to escalations. While the agent initiates 1,000 interactions, only 650 are successfully completed. The $2.31 cost per outcome includes the platform fee and the two minutes of human review required for each accepted result.
Escalations and human review are integral to the true cost of AI. In this model, 35% of interactions require human intervention. By tracking these escalations, organizations can ensure that the labour value of time saved reflects realized gains rather than theoretical estimates.
NetLift measures the deterministic time saved against objective baselines to determine if agent spend actually pays back. We rank Evidence Quality from Estimate Only to Verified, ensuring the $4,458 monthly net value is grounded in tracked work. This data allows leaders to move beyond hype and decide whether to Expand or Review a deployment based on the cost of successful outcomes versus manual effort.
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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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