Why Traditional SaaS Pricing Doesn't Work for AI Products
Per-seat pricing made sense for dashboards. For AI agents that do actual work, the value equation is different.
Ersel Gökmen
December 22, 2025
SaaS pricing has been stable for a decade: per-seat, per-month, tiered by features. It works when the value scales with users — more people using Slack means more value.
AI products break this model. The value doesn't come from how many people log in. It comes from how much work the agent does.
The Agent Economics
A traditional analytics tool costs $50/user/month. 10 users = $500/month. The value is proportional to eyeballs on dashboards.
An AI agent that saves a buyer 15 hours/week and prevents $50K in markdown waste doesn't care how many seats you have. One seat, ten seats — the agent does the same work.
Value-Based Pricing
The right pricing model for AI products is outcome-based. Not "how many people use it" but "how much value does it create?" A percentage of savings, a per-analysis fee, or a flat rate that's obviously ROI-positive.
We're still figuring this out at Mondian. But we know the answer isn't $50/seat/month for a tool that replaces a $80K analyst.