In my recent episode of Run the Numbers with CJ Gustafson, we explored what happens when traditional software pricing models meet the realities of AI.
For decades, software pricing was predictable: sell more seats, add more margin, and scale efficiently. But with AI, every usage prompt has a real cost, and that breaks the old economics.
🎧 Watch the full episode:
https://www.youtube.com/watch?v=qNn9_07efN4&t=956s
Why AI Is Breaking Traditional Pricing Models
AI has completely changed how value is delivered and measured. What once scaled cheaply now requires significant compute power. Your product might look like software, but it behaves like infrastructure.
This shift forces every company to rethink how they define value, allocate costs, and communicate fairness to customers. Predictable, seat-based models are being replaced by usage-based approaches that create both new opportunities and new headaches.
The Hidden Trade-Offs of Value-Based Pricing
Value-based pricing has become a popular mantra, but it is not always as customer-friendly as it seems.
As AI makes certain features feel commoditized or “free,” pricing power can erode overnight. Many companies are realizing that customers pay for perceived value, not technical complexity.
The real challenge is not just setting the right price. It is understanding what customers truly value when that perception can change by the day.
Real-World Pricing Chaos
Pricing theory is one thing. Reality is another.
The AI era has introduced a new level of uncertainty in how companies measure value and prove ROI. Pricing now requires equal parts data, psychology, and adaptability.
In other words, the spreadsheet alone will not save you.
Related Insights
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