The ROI of a coding agent is determined by the net staff time saved after accounting for human review and escalations. For an agent handling 1,000 monthly interactions with a 65% success rate, the business realizes 108 hours of net time saved. At a loaded staff cost of $55 per hour, this generates a monthly labor value of $5,958.
To find the true net value, platform costs must be subtracted from the labor savings. With a $1,500 monthly fee, the current net value stands at $4,458. This calculation treats escalation and rework as part of the true cost, ensuring the financial return reflects actual work completed rather than just tool usage.
Agent ROI worked example
Worked example for Coding 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.
What is the true cost per successful outcome?
The true cost of an AI-generated outcome includes the platform subscription and the human time required to review it. Based on 650 successful monthly outcomes, the cost per successful outcome is $2.31. This metric is critical because an agent that resolves fewer tasks but requires less rework can often be more cost-effective than a high-volume agent with a high failure rate.
How do escalations impact ROI?
Escalations represent work the agent could not complete, which in this case accounts for 35% of interactions. Tracking these escalations alongside the two minutes of human review required per accepted outcome allows leaders to see the net staff time saved—108 hours per month—rather than just a gross productivity estimate. This helps in making a data-driven decision to Expand, Continue, or Review the deployment.
NetLift measures this value by comparing the time work takes with AI against established baselines. By calculating the labour value of realized time saved minus the full AI cost, we assign an Evidence Quality grade to the data. This allows organizations to manage AI spend based on verified work outcomes rather than individual monitoring or surveillance.