
Pricing AI: Outcome-Based Pricing – The Holy Grail for AI
Buyers do not care how many tasks your AI performs or how many tokens it consumes. They care about results. In B2B, results show up

Buyers do not care how many tasks your AI performs or how many tokens it consumes. They care about results. In B2B, results show up

Pricing AI is hard because no single metric captures how value is created and how costs behave. A per-user fee feels simple but ignores automation.

Pricing metrics shape how buyers perceive value and how companies capture it. Choosing the right one is one of the hardest decisions in any business,

With SaaS, per-seat pricing was simple, predictable, and familiar to buyers. It became so common that many equated “SaaS pricing” with “seat-based pricing.” But AI

Every day a new vendor pops up promising “AI powered” this or “machine learning” that. Budgets are being carved out, boards are asking about AI

You can listen to the full audio version of this blog we call — Blogcast. You’re sitting in a conference room facing a software purchase decision.

You can listen to the full audio version of this blog we call — Blogcast. I got so excited last week to dive into how to

You can listen to the full audio version of this blog we call — Blogcast. The value architecture has three layers: foundational problems, problem scope, and

Mark, Why Does This Distinction Matter? In AI, whether you are selling a platform or a solution is one of the most important strategic decisions

You can listen to the full audio version of this blog we call — Blogcast. Buyers trade money for value. They don’t care what it takes