How to get your AI pricing strategy right
Stripe just dropped some shocking data: 73% of companies have changed their pricing model two or more times in the last few years.
If you're still charging a flat monthly fee for your AI product, you're not just leaving money on the table, you're actively losing customers who can't afford your Western-priced solution while subsidizing power users who should be paying more.
Here's what the smartest AI companies are doing instead.
Table of Contents
The Death of One-Size-Fits-All Pricing
Stripe's latest research reveals a massive shift happening right now:
- Only 15% of companies still use pure subscription pricing
- 56% of AI companies have already moved to hybrid models
- 70% of software companies are planning to add usage components soon
The companies still charging everyone $29/month are becoming dinosaurs. While they're stuck with predictable but limited revenue, smart competitors are capturing both reliable subscription income AND scaling usage revenue.
Why Traditional Models Are Failing AI Companies
Stripe identified three critical problems with traditional pricing for AI:
1. Complex Value Propositions
Your AI tool might help someone write a quick internal email or generate a million-dollar marketing campaign. Same feature, completely different business impact. Charging the same price for both scenarios feels unfair to customers and limits your revenue potential.
2. Variable Costs That Scale With Usage
Unlike traditional software, every AI action costs real money. Your GPT API calls, image generation, and data processing create variable costs that flat pricing can't handle. Power users destroy your margins while light users overpay and churn.
3. Rapidly Evolving Landscape
What's revolutionary today becomes commoditized next week. Companies need pricing models that can adapt without rebuilding their entire billing system.
The Stripe Framework That's Changing Everything
Stripe's five-step framework is being used by the fastest-growing AI companies:
Step 1: Define Your Value Metric
Stop thinking about what your product does. Start thinking about what problems it solves:
- Automation: How much time does your AI save customers?
- Augmentation: How much better are the results your AI produces?
- Outcomes: What specific business results does your AI deliver?
Step 2: Create Your Charge Metric
Your charge metric should align with both customer value AND your costs:
- Consumption-based: Charge for tokens, API calls, compute time
- Workflow-based: Charge per document analyzed, image generated, report created
- Outcome-based: Charge for leads generated, tickets resolved, conversions driven
Step 3: Choose Your Model
Stripe's data shows hybrid models are winning:
- Predictable base fee (keeps investors happy with recurring revenue)
- Usage-based scaling (aligns price with value delivered)
- Smart guardrails (prevents bill shock and abuse)
Step 4: Implement Guardrails
- Usage caps: Cut off access at spending limits
- Automated notifications: Warn users about approaching limits
- Rate limiting: Prevent abuse and overuse
Step 5: Iterate Constantly
Your first pricing model is a hypothesis. The companies winning treat pricing like a product, constantly testing and improving based on customer feedback.
How to Implement This for Your Global Business
Here's where most AI companies miss a massive opportunity: they implement sophisticated usage-based pricing but still charge the same amount globally.
The reality check:
- Your $97/month AI tool costs the equivalent of $400+ for someone in Bangladesh
- Your pay-per-token model might be affordable in San Francisco but prohibitive in São Paulo
- You're building the perfect pricing structure but only monetizing 15% of the global market
The solution: Combine Stripe's framework with geographical pricing intelligence.
The Smart Approach:
- Implement hybrid pricing using Stripe's framework
- Add geographical intelligence to show different prices based on purchasing power
- Protect against abuse with VPN detection and fraud prevention
- Monitor and optimize performance across different regions
This is exactly what tools like Evendeals enable, sophisticated location-based pricing that works with any billing system, including Stripe's usage-based models.
You get the best of both worlds:
- Stripe's sophisticated usage-based billing
- Geographical pricing that maximizes global revenue
Implementation in Minutes, Not Months
While Stripe handles the complex billing logic, Evendeals handles the geographical optimization:
- Detect visitor location automatically
- Display appropriate pricing based on purchasing power
- Integrate seamlessly with your existing Stripe setup
- Track performance across regions and pricing models
The Bottom Line
Stripe's research proves what smart AI companies already know: the future belongs to hybrid models that balance predictability with fairness.
But there's a second layer most companies miss: geographical optimization.
The companies dominating tomorrow's market are doing both:
- Implementing sophisticated usage-based pricing (using tools like Stripe)
- Optimizing that pricing for global markets (using tools like Evendeals)
While your competitors debate between $29/month and pay-per-use, you could be capturing revenue from:
- Predictable subscription income in high-value markets
- Usage-based scaling for power users
- Geographically-optimized pricing for emerging markets
- Smart guardrails preventing abuse and bill shock
The question isn't whether this approach works, Stripe's data proves it does.
The question is: how much longer can you afford to use yesterday's pricing model in tomorrow's market?
Every day without hybrid pricing is revenue left on the table. Every day without geographical optimization is billions of potential customers turned away.
Ready to implement both? Start with Evendeals' free plan to test geographical pricing optimization, then scale with Stripe's usage-based billing as you grow.
The future of AI pricing isn't subscription OR usage-based OR geographical, it's all three, working together.
Try Evendeals Free