Is usage-based pricing becoming the norm for AI tools?
Hey everyone,
I've built my product around traditional SaaS pricing (monthly tiers), but I’m starting to wonder if that model is getting outdated, especially with more AI-powered and compute-heavy tools entering the market.
That shift requires real architectural changes, instrumentation, metering, billing logic, and UI changes, not just pricing tweaks. It’s something I’m starting to seriously think about for my own product.
In particular, AI usage has real COGs (every prompt costs money), and I’m seeing more platforms experimenting with usage-based models, or hybrids like “SaaS base + usage + overage.”
For those of you building AI or compute-intensive tools:
Are you sticking with SaaS pricing?
Have you considered switching to usage-based or hybrid models?
Is it helping or hurting conversions?
Would love to hear what others are doing and whether you're seeing buyer preferences shift, too.
Replies
tbh I think usage shouldn't be punished, SaaS pricing was succesful because everybody understood what would pay. I understand token consumption can be costly for AI-tools, but they should route 2 different models, one static SaaS subscription and one hybrid per usage, which will focus on users that actually cost them a lot of money, they need internal scoring based on different use-cases, and route users based on that. (I think).
The problem with usage-based is it makes people ration. If every run costs, they stop experimenting, and experimenting is how they find out the tool is worth keeping.
We'd rather eat some margin early and have people actually use it. Metering is honest, but it teaches the wrong habit in month one.