AI Returns & Unit Economics Evaluator

Workflow & Unit Assumptions

Monthly Task Volume: 250,000

Human Baseline Cost / Task ($): $6.50

Automation Accuracy Rate (%): 78%

Human Review Cost / Failed Task ($): $8.20

Input Tokens / Task

Output Tokens / Task

Input Rate ($/1M Tok)

Output Rate ($/1M Tok)

Monthly Infra/Tooling ($)

Maint. & Eng ($/mo)

Net Monthly Economic Benefit
$1,105,625.00
+$4.42 net / task

Total AI Operating Cost

$519,375.00

$2.08 blended / task

Unit ROI

212.88%

Return on AI OPEX

Breakeven Monthly Volume

17,887 tasks

7.2% of curr. volume

Monthly Financial Decomposition Waterfall

1. Baseline Labor Cost (Replaced) $1,625,000.00

2. Direct Model Inference Cost (Tokens) $1,375.00 (0.1%)

3. Human Escalation & Verification (22% Failures) $451,000.00 (27.8%)

4. Fixed Platform, Observability & Eng Overhead $67,000.00 (4.1%)

5. Net Realized Business Value $1,105,625.00 (68.0%)

Unit Economics & Sensitivity Ledger

Scale Tier	Volume	Inference Cost	Escalation Cost	Fixed Amort.	Total Cost/Task	Net ROI

Methodology: Evaluates total cost of ownership (TCO) beyond raw LLM API consumption. Incorporates human-in-the-loop review penalties ($ / failed task routing), fixed tooling amortizations, and labor displacement thresholds to deliver verifiable bottom-line enterprise returns.