How to Use AI vs Human Support Cost
Computes human-only baseline cost vs an AI-first model where unresolved tickets escalate to humans with overhead. Outputs per-ticket cost, monthly savings, and savings %.
What It Does
Use the calculator with intent
Computes human-only baseline cost vs an AI-first model where unresolved tickets escalate to humans with overhead. Outputs per-ticket cost, monthly savings, and savings %.
Support leaders, ops teams, and founders evaluating AI-deflection tools.
Interpreting Results
Negative savings means escalation overhead and AI cost outweigh deflection. Push resolution rate up by improving retrieval; lower token cost with smaller models or caching.
Input Steps
Field by field
- 1
Total
Total monthly ticket volume.
- 2
Average
Average handle time. Use median, not mean — outliers distort.
- 3
Loaded
Loaded rate (wage + benefits + tooling). BLS pegs CSR median around $19/hr in 2024; loaded is 1.4 to 1.8×.
- 4
Fraction
Fraction of tickets the AI agent fully resolves without escalation.
- 5
Average
Average input + output tokens per AI-handled ticket. Add tool-call overhead.
Realistic AI token counts are 2 to 10× a single QA-style request.
Common Scenarios
Use realistic starting points
E-commerce volume
Tickets / mo
30000
Savings dollar value scales linearly with volume; 10k+ tickets/mo usually justifies AI.
Complex B2B
Avg human minutes
25
Lower resolution rate, but high human handle time still favours AI for tier-1.
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FAQ
Questions people ask next
The short answers readers usually want after the first pass.
Sources & References
- BLS — Customer Service Representatives wages 2024 — U.S. Bureau of Labor Statistics
- Zendesk CX Trends 2024 — Zendesk
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