What is AI Unit Economics?
AI Unit Economics measures the per-interaction profitability of AI-powered features.
AI Unit Economics measures the per-interaction profitability of AI-powered features. Unlike traditional software with near-zero marginal costs, AI features have significant variable costs — every API call, every inference request, every token processed costs money.
The AI Unit Economics Formula: Revenue per AI interaction − Cost per AI interaction = Margin per interaction
Costs include: LLM API fees, embedding generation, vector database queries, retrieval pipeline compute, post-processing, monitoring, and error handling. Many AI features are margin-negative — they cost more to serve than the revenue they generate.
Richard Ewing's AUEB (AI Unit Economics Benchmark) calculator at richardewing.io/tools/aueb helps teams model these economics before and after launch.
Why It Matters
Most AI product failures are economic, not technical. Teams build impressive AI capabilities without modeling whether the feature can be profitable at scale. The AUEB tool prevents the most expensive mistake in AI product development.
How to Measure
Calculate fully loaded cost per AI interaction (API + compute + retrieval + monitoring). Compare to revenue per interaction. Track margin trend over time.
Frequently Asked Questions
What percentage of AI features are margin-negative?
Industry estimates suggest 60-80% of AI features in production are margin-negative when fully loaded costs are included.
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Richard Ewing is a Product Economist and AI Capital Auditor. He helps companies translate technical complexity into financial clarity.
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