Agent ROI Calculator
Compare the cost of AI agents against human workers. Estimate savings, ROI, and break-even timelines for automating roles with AI.
Accounts for benefits, taxes, overhead (typically 1.2x -- 1.5x)
Total input + output tokens
Results
$234,000
40% of $585,000
$1,236
$102.96/month
$232,764
Agents are cheaper
+19k%
Break-even: ~1 mo
| Metric | Year 1 | Year 2 | Year 3 | Total |
|---|---|---|---|---|
| Human Cost | $234,000 | $234,000 | $234,000 | $702,000 |
| Agent Cost | $1,441 | $1,236 | $1,236 | $3,912 |
| Net Savings | $232,559 | $232,764 | $232,764 | $698,088 |
Year 1 agent cost includes a 2x monthly ramp-up/integration overhead. Human costs held constant (no raises modeled). Agent costs assume stable API pricing.
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Salary data based on US averages for the given roles. Model pricing sourced from public API documentation as of early 2025. Actual costs may vary based on region, seniority, negotiated API pricing, caching, and batch discounts.
About This Tool
Return on investment is the ratio of net gain to initial cost, expressed as a percentage. For AI agent deployments, the gain is typically labor hours saved or revenue lifted, less the recurring inference, vendor, and oversight costs.
This calculator weighs projected savings against deployment spend to produce ROI percentage and payback period. Inputs cover license fees, per-task costs, headcount displaced or augmented, and the time horizon you want to model.
The underlying math is straightforward. Net benefit equals (savings + new revenue) minus (license + inference + integration + oversight). ROI is net benefit divided by total cost, multiplied by 100. Payback period is total cost divided by monthly net benefit. Where it gets messy is the savings side. Hours saved per task multiplied by tasks per month multiplied by fully loaded labor cost gives a top-line figure, but real organizations rarely capture every hour as actual cost reduction. A team that saves 200 hours a month doesn't shrink by one headcount unless management acts on the slack — and most don't.
A worked example. A 50-person customer support team handles 10,000 tickets a month. An agent deflects 30% (3,000 tickets) at an average of 8 minutes per ticket, saving 400 hours. At a fully loaded cost of $45/hour, that's $18,000/month gross savings. Inference cost at $0.02 per ticket is $60/month. Platform license is $2,000/month. Initial integration runs $40,000 one-time. Net monthly benefit: $15,940. Payback: about 2.5 months. ROI over year one: roughly 380%.
Limitations worth naming. The calculator assumes the savings figure is real — that those hours either reduce headcount, defer hires, or get redeployed to revenue work. If they just produce slack, the financial gain is roughly zero even though the model says otherwise. It also ignores the cost of failure: agents make errors, errors cost more than human errors when they reach customers, and the maintenance overhead of keeping prompts and tools current is rarely budgeted. Treat the output as a financial ceiling for optimistic cases and a floor for honest ones, depending on which side of the assumptions you're on.
The about text and FAQ on this page were drafted with AI assistance and reviewed by a member of the Coherence Daddy team before publishing. See our Content Policy for editorial standards.