How to Price an AI Agent: Why it can be Mathematically Right and still Backfire (Part 2 of 2)
Charging a percentage of value delivered can be mathematically perfect and still cost you your biggest accounts — the math isn't the problem, the psychology is.
Outcome-based pricing can pass every framework test — COMPASS-approved, highly attributable, exactly the model the math says you should use — and still fail with your largest accounts. As an enterprise grows and its exposure grows, the fee grows right along with it, turning success into what starts to feel like a tax. Large enterprises expect better economics as they scale, not worse, so a model that reverses that expectation is hard to justify internally — and it's exactly the opening a flat-rate competitor needs. This piece walks through four structural fixes — capping the fee, tiering the percentage down, blending base and outcome pricing, and making the calculation jointly auditable — that let you keep the economics of outcome-based pricing without triggering the psychology that breaks it.
Read the full article on LinkedIn → here
