AI SaaS Pricing Strategies: How to Price Your AI Product

Pricing is the most powerful growth lever—yet most AI companies get it wrong.

The AI Pricing Challenge

AI products are different:

- **Variable costs**: API calls, compute, tokens

- **Perception of value**: Hard to quantify AI's contribution

- **Competition**: Racing to the bottom on price

Common Pricing Models

1. Per-Seat Pricing

**Best for**: AI tools with clear user workflows

**Example**: Notion AI charges per user

2. Usage-Based Pricing

**Best for**: API products, developer tools

**Example**: OpenAI charges per token

3. Credit System

**Best for**: Mixed workloads, enterprise

**Example**: Credits that can be used across features

4. Outcome-Based Pricing

**Best for**: High-value, measurable outcomes

**Example**: Charge based on revenue generated

Our Recommended Framework

1. **Calculate your costs**: Include API, compute, support

2. **Estimate value created**: What's the ROI for customers?

3. **Price at 10-20% of value**: Leave room for clear ROI

4. **Test and iterate**: Pricing is never done

Common Mistakes

- Pricing too low (leaving money on the table)

- Complex pricing (confusing buyers)

- Ignoring variable costs (margin erosion)

- Not offering enterprise tier (losing big deals)