Scenario B: 15-minute screening time
Scenario B models optimized recruitment operations where human recruiters have streamlined their screening process to 15 minutes per application. This represents a 66% efficiency improvement over Scenario A. This scenario maintains the same fully loaded annual cost of $112,250 for a mid-level recruiter. However, it demonstrates significantly enhanced human productivity, with daily capacity increasing to 32 applications during an 8-hour shift and monthly throughput reaching 660 applications. The improved human efficiency reduces the cost per application from $45 to $15, narrowing the economic gap with the agentic AI system. However, the agent maintains its structural advantages: 5-minute processing time, 24/7 availability enabling 288 daily applications, a lower 2% error rate compared to the human 5%, and monthly capacity exceeding 8,600 applications. While this efficiency improvement extends the break-even period from 1.16 months to 4.76 months and reduces monthly savings from $19,833 to $4,833, the analysis reveals that agent systems remain economically viable even when competing against highly optimized human operations—a critical insight for organizations evaluating whether their current process efficiency levels justify agentic AI investment.
Base cost structure
The following table shows annual fixed costs for scenario B.
Component |
Human operations |
Agentic AI system |
|---|---|---|
Base Salary |
$65,000 |
N/A |
Benefits (30%) |
$19,500 |
N/A |
Workspace & Equipment |
$12,000 |
N/A |
Management Oversight (15%) |
$9,750 |
N/A |
Training & Development |
$6,000 |
N/A |
Total Annual Fixed Cost |
$112,250 |
N/A |
The following table shows implementation costs for scenario B.
Component |
Human operations |
Agentic AI system |
|---|---|---|
Initial setup |
N/A |
$23,000 |
Monthly fixed costs |
$9,354 |
$500 |
Operational metrics
The following table shows operational metrics for scenario B.
Metric |
Human operations |
Agentic AI system |
|---|---|---|
Processing time per application |
15 minutes |
5 minutes |
Hourly capacity |
4 applications |
12 applications |
Daily capacity (8-hour shift) |
32 applications |
288 applications |
Monthly capacity |
660 applications |
8,640 applications |
Cost per application |
$15 |
$2.50 |
Cost per successful hire |
$2,200 |
$125 |
Error rate |
5% |
2% |
Error correction cost |
$30 per error |
$45 per escalation |
Volume-based cost analysis
The following table shows a volume-based cost analysis for scenario B. In this example, the agentic AI system cost includes fixed costs and amortized setup costs of $1,917 per month over 12Â months.
Monthly volume |
Human cost |
Agentic AI system cost |
Monthly savings |
|---|---|---|---|
100 applications |
$1,500 |
$750 |
$750 |
500 applications |
$7,500 |
$2,667 |
$4,833 |
1,000 applications |
$15,000 |
$4,917 |
$10,083 |
ROI analysis
The following table shows an ROI analysis for scenario B that is based on processing 500 applications per month.
Metric |
Value |
|---|---|
Monthly human cost |
$7,500 |
Monthly agentic AI system cost |
$2,667 |
Monthly savings |
$4,833 |
Annual savings |
$57,996 |
Break-even period |
4.76 months |
Cumulative cost comparison
The following table shows a cumulative cost comparison for scenario B for the first six months, assuming 500 applications per month.
Month |
Human cost |
Agentic AI system cost |
Cumulative savings |
|---|---|---|---|
1 |
$7,500 |
$25,667 |
-$18,167 |
2 |
$15,000 |
$28,334 |
-$13,334 |
3 |
$22,500 |
$31,001 |
-$8,501 |
4 |
$30,000 |
$33,668 |
-$3,668 |
5 |
$37,500 |
$36,335 |
$1,165 |
6 |
$45,000 |
$39,002 |
$5,998 |
