Credit-based pricing nearly doubled in a year, and buyers are budgeting 25-35% more

Per McKinsey's 2026 software pricing data, 62% of SaaS platforms have introduced AI-premium tiers, and credit-based pricing nearly doubled year over year, from 35 companies to 79. HubSpot, Figma, Adobe, Salesforce, and Cursor have all moved to credit models. Buyers report budgeting 25% to 35% more when they bolt AI onto an existing stack. (Monetizely)

Credits are the compromise nobody loves and everybody's adopting. Pure per-seat pricing breaks the moment a customer's agents start burning inference at unpredictable rates, because the vendor eats the variable cost. Pure usage metering terrifies buyers who can't forecast a bill. Credits split the difference: you sell a predictable-ish bucket, the customer pre-commits, and the vendor gets to charge more for AI without nuking the subscription line item that finance teams understand.

The forcing function underneath is margin. Vendors charging flat per-seat fees for AI features post roughly 40% lower gross margins than competitors who pass compute through via usage or outcome pricing, because the per-seat folks absorb inference cost themselves. (SaaS Mag) That gap is now a board-level number, which is why even vendors who philosophically prefer seats are being dragged off them.

If you're pricing an AI product, the lesson is that pricing is now a margin-survival decision, not a packaging preference. Flat per-seat for an inference-heavy feature is a slow bleed. But credits have their own trap: if your credit-to-value mapping is opaque (and most are, deliberately), you train customers to resent every action that "costs credits," which kills the engagement you actually want. The buyers budgeting 25-35% more are giving you room, for now. That tolerance won't last once they can compare credit economics across vendors. Price the outcome if you can measure it. Price credits if you can't. Don't price seats for anything that calls a model.