Inference Cost
Working knowledgeAI Economics and Infrastructure
Inference cost is the cost of actually running an AI model to produce an output. Training a model is expensive and happens once; inference happens every time the model is used, and at scale it becomes the dominant cost line. A deployment that looks economical in a pilot can become financially significant when rolled out across daily operations.
In practice
Understanding inference cost is the difference between an AI business case and an AI P&L surprise. Model it per transaction at expected volume before signing rather than per seat, and re-check it whenever the workload changes, because a longer prompt or a model that thinks for longer both move the number.