Pricing AI: Finding the Right Metric for Value

How should companies price AI products when usage, costs, and customer value can vary so dramatically?

In this episode of the LogiSense podcast, pricing expert Mark Stiving joins Tim Neil to discuss AI pricing, AI monetization, usage-based pricing, hybrid pricing, credits, tokens, and the challenge of choosing the right pricing metric.

As AI changes the economics of software, many companies are experimenting with token-based pricing, consumption-based models, credits, subscriptions, and outcome-based pricing. But according to Mark, the fundamentals of pricing have not changed: customers are still willing to pay based on the value they receive. The challenge is finding a pricing metric that reflects that value while also accounting for the very real infrastructure and compute costs associated with AI. 

For companies building AI products, SaaS platforms, AI agents, cloud services, or other consumption-based offerings, the discussion highlights an important principle: the metric you choose to charge for may be one of the most important monetization decisions you make.