Traditional enterprise software charges by the seat: a fixed fee per named user, regardless of how much or how little that person actually uses the product in a given month. Usage-based pricing replaces that fixed unit with a variable one tied to actual consumption, tokens generated, API calls made, minutes of audio produced, documents processed, so the bill moves with real activity rather than headcount.
The shift matters most for AI products because seat pricing and AI capability pull against each other. A seat-priced assistant that gets good enough to replace the work of several people sees its own addressable revenue shrink as customers need fewer licences, exactly when the product is performing best. Usage-based pricing removes that perverse incentive: the vendor’s revenue grows in step with how much work the AI actually completes, not with how many humans are still around to hold a login.
The practical tell is in the contract, not the marketing. If a vendor’s price list has no volume or consumption tier, and scales only with named users, treat any claim of “outcome-driven” or “AI-native” pricing with scepticism, because the underlying incentive still runs through seats, not through work done.