AI Compute Costs Drive Shift To Usage-Based Software Pricing
The software-as-a-service (SaaS) industry is evolving, moving away from the traditional “per seat” licensing model to embrace usage-based pricing structures. Reports indicate that this shift is largely driven by the skyrocketing compute costs linked to the new reasoning AI models that underpin modern enterprise applications.
These reasoning models execute complex computations during inference, dramatically increasing both token usage and operational costs. For instance, OpenAI’s recent models reportedly require 1,000 times more tokens compared to older versions, with a single benchmark response costing approximately $3,500, as noted by Barclays.
Companies such as Bolt.new, Vercel, and Monday.com have already started adopting usage-based or hybrid pricing models that align costs with AI resource consumption. Meanwhile, ServiceNow, which primarily uses a seat-based pricing model, has introduced usage meters for high-consumption scenarios, highlighting the push for flexibility in pricing as demand for AI escalates.
Key Points
- The SaaS industry is shifting from “per seat” pricing to usage-based models due to rising AI compute costs.
- New reasoning AI models significantly increase operational expenses through extensive token usage.
- Companies like Bolt.new, Vercel, and Monday.com are leading this pricing evolution by linking costs to AI resource consumption.
- ServiceNow is integrating usage meters in its pricing strategy while retaining a seat-based approach for predictability.
- The demand for AI is pushing companies to adopt more flexible pricing structures to manage costs effectively.
Why should I read this?
If you’re involved in tech or software services, you’ll want to know how AI is reshaping pricing strategies. This article sheds light on a significant shift that’s altering how companies think about cost structures, making it a must-read to stay ahead of the curve and understand where your industry might be heading next!