In a recent video titled "AI Pricing Is Broken | Here's the Shift Every SaaS Founder Is Missing," Akhil from Monetizely explores the fundamental problem with current AI pricing models. Referencing a Diginomica article on commodifying AI compute, he argues that most companies are focusing on the wrong question when it comes to AI monetization.
The Real Problem with AI Pricing
"Most companies are solving the wrong problem," Akhil states. "They are obsessed with how to price AI, usage-based, per seat, hybrid models and whatnot. But they are missing the fundamental what are you actually selling?"
This insight cuts to the heart of a growing issue in enterprise technology. According to Akhil, IT leaders are experiencing significant budget overruns from AI costs, not because the technology isn't valuable, but because the pricing models are fundamentally misaligned with customer needs.
Selling Kilowatts When Customers Just Want Lights
The most compelling analogy Akhil offers compares current AI pricing to electricity:
"When you buy electricity, you do not care about kilowatts. You care about keeping the lights on. But right now, AI vendors are selling kilowatts."
This disconnect between what vendors are selling (compute power, API calls, tokens) and what customers are buying (business outcomes, productivity gains, problem-solving) creates friction in the market. It's a fundamental misalignment that's causing pain on both sides of the transaction.
What's Actually Working in AI Pricing?
Data shows that not all approaches to AI monetization are created equal. According to Akhil's analysis:
"Hybrid pricing models are delivering 21% median growth, crushing pure usage or subscription models."
The reason? Hybrid models balance predictability with value capture. They provide customers with some cost certainty while still allowing vendors to share in the upside when their solutions deliver exceptional value.
The Evolution Beyond Commodity Compute
The most forward-thinking companies in the AI space are already moving beyond selling raw compute:
"Commoditizing compute is just step one. The real opportunity is in packaging intelligence as a service."
This represents a fundamental shift in how AI capabilities are positioned and sold. Instead of focusing on the underlying technology, these companies are creating pricing tiers based on the business outcomes their solutions enable.
"The smartest players are creating pricing tiers based on business outcomes, not API calls. They are selling productivity gains, not processing power."
The Future of AI Pricing: More Like Insurance Than Utilities
Perhaps the most intriguing prediction Akhil makes is about where AI pricing is headed:
"Within 18 months, we will see AI features priced like insurance. You will pay for the value of problem solved, not the compute consumed."
This insurance-like model represents a complete transformation in how we think about technology pricing. Rather than paying for resources consumed, customers would pay based on the risk mitigated or the value of the problem being solved.
How to Get Ahead of the Shift
For SaaS leaders and product teams integrating AI capabilities, Akhil offers a clear recommendation:
"Start measuring business impact of your AI features today. That's your future pricing metric."
This advice is particularly valuable because it's actionable immediately, even before you change your pricing model. By understanding the true business impact your AI features deliver, you can begin the process of aligning your pricing with the outcomes customers actually care about.
The Bigger Picture: A Fundamental Shift in Software Economics
What makes this topic particularly significant is that it represents more than just a tactical pricing decision – it's part of what Akhil describes as "the biggest shift in software economics since SaaS was born."
Just as the transition from perpetual licenses to subscription models fundamentally changed the relationship between vendors and customers, this shift toward outcome-based AI pricing has the potential to transform how technology is sold, deployed, and valued.
For SaaS executives navigating this shift, the message is clear: the winners won't be those with the cleverest usage metrics, but those who successfully abstract away the complexity of AI and sell the business outcomes their customers actually care about.
How Is Your AI Pricing Model Performing?
If you're integrating AI capabilities into your products, it's worth asking: are you selling kilowatts or keeping the lights on? Are you measuring and pricing based on compute consumed or problems solved? The answer may determine whether your AI strategy leads to budget overruns or breakthrough growth.
The companies that figure out this pricing puzzle first will likely gain a significant advantage in what promises to be the next major evolution of the software industry.