Introduction

AI tools cost money every time people use them. This article explains why old SaaS pricing fails and what pricing works now.

What's the problem it solves?

AI companies pay for usage every time customers use their product. If pricing ignores these costs, growth can destroy margins and bankrupt the business.

Quick Summary

Traditional SaaS worked because more users did not add much cost. AI breaks this model. Every prompt, image, or action costs real money because companies pay LLM providers per use. Growth is no longer free.

Many AI startups copied old subscription pricing and got burned. Some lost money on their best customers. The article explains five pricing models that can survive AI costs and shows where each one works best.

The key shift is that pricing is no longer just a finance decision. Engineering, product, and growth teams must design pricing together so usage, value, and costs stay aligned.

Key Takeaways

• AI makes marginal costs real again
• Flat subscriptions can destroy margins in AI products
• Pricing must match both cost structure and customer value
• Credits and usage limits help control runaway usage
• Pricing is now a product and engineering problem, not just finance

What to do

• Map your real AI costs per user action
• Choose a pricing model that scales with value, not hype
• Add guardrails like limits, credits, or overages
• Involve engineering in pricing decisions early
• Test pricing before growth exposes hidden cost problems

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