AI features cost real money to operate. Every GPT-4 call has a price. Without thoughtful AI pricing, you'll either lose money on power users or price out customers who would have paid for a more accessible option. Here's how to structure AI pricing in your SaaS.

The Challenge with AI Pricing

Standard SaaS features cost nearly the same to run regardless of usage — a project management feature costs similar compute whether a user creates 10 projects or 100. AI features are variable-cost: more usage = more API spend. This variable cost must be reflected in how you charge.

Model 1: Credit System

Allocate AI credits per plan: Starter = 100 credits/month, Pro = 500 credits/month, Business = unlimited. Each AI operation costs a defined number of credits (1 credit for a short summary, 10 credits for a full document analysis).

Pros: Simple to understand, easy to upsell credits, scales with your costs.

Cons: Users may find credits confusing or feel artificially limited.

Model 2: Feature-Based Limits

Instead of abstract credits, limit AI features by count: "Generate up to 50 AI reports/month on Pro." This is more intuitive than credits because users understand "reports" better than "tokens."

Model 3: AI on Premium Tier Only

Keep all AI features on a premium tier that costs meaningfully more than the standard tier. Simple Pro ($49) has no AI. Advanced Pro ($99) has AI. This lets customers who don't need AI stay at a lower price point while capturing more value from AI power users.

Overage Charges

When users exceed their monthly AI allocation, they can: upgrade their plan, purchase additional credits as a one-time add-on, or wait until next month's allocation resets. Stripe's metered billing makes overage charges straightforward to implement.

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Communicate Limits Clearly

Always show users their AI usage in the product: "You've used 340 of 500 AI credits this month. Resets in 12 days." Never surprise users with limits they didn't know existed — surprise limits are the fastest way to earn negative reviews.