How to Estimate GenAI Implementation Costs
A method for costing a generative AI implementation across development, data, infrastructure and ongoing operation.
Break the estimate into phases
Discovery and design, build and integration, data preparation, security and governance, deployment, and ongoing operation. Each phase has distinct cost drivers and distinct risks of being underestimated.
One-time build costs
Solution development, integration with existing systems, prompt and workflow engineering, evaluation harnesses, and the governance and security review required before production.
Recurring operating costs
Model or API consumption at expected volume, inference or hosting infrastructure, monitoring, human oversight, and periodic re-evaluation as models and data change.
Estimate consumption from volume
For token-based costs, estimate expected requests, average input and output size, and unit price, then stress-test against a higher-adoption scenario. Consumption is the cost most sensitive to success.
Add a contingency
Early GenAI estimates carry real uncertainty. A named contingency is more honest than a precise-looking figure that ignores it.
Put this into practice.
Run the numbers for your own initiative in the free AI ROI calculator.