AI usage may grow without producing a corresponding business benefit. Unit economics helps teams compare the complete cost of an AI workload with how much it is used and the outcomes it delivers.
Choose the right unit
|
Metric |
Use it to understand |
|---|---|
|
Cost per 1,000 tokens |
Model consumption cost |
|
Cost per request |
Application and model serving efficiency |
|
Cost per active seat |
Adoption relative to licence cost |
|
Cost per verified outcome |
Cost of a completed business result |
|
Value per dollar |
Measured benefit relative to the defined investment base |
These are possible management measures, not fixed metrics that will appear in every Yarken environment. Their availability depends on source data, configured reports, and agreed definitions.
Build a meaningful comparison
-
Choose one AI product, feature, service, or workflow.
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Identify all direct and allocated costs for the reporting period.
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Select a usage or outcome measure that can be verified.
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Calculate the unit metric using consistent definitions, such as fully loaded cost ÷ verified outcomes.
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Compare the result with the budget, previous periods, or comparable initiatives.
Example: For an AI customer-support workflow, measure total attributed cost against successfully resolved cases. Requests and tokens explain consumption; resolved cases help explain business value.
Connect value to decisions
Track outcomes such as time saved, cases resolved, revenue supported, quality, or productivity when these are measured and attributable. Use Investment Planning and Business Cases for the original assumptions and Analytics for available actuals and trends.
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