Olivier Dallemagne tackles the issue of AI pricing mistakes and explains how to improve execution, monetization, and how to avoid false progress.
Should AI reinvent your business model—or first help you see the price your customer can actually absorb?”
The pressure is back — and the reflex is wrong
The biggest AI pricing mistake is not moving too slowly.
It is asking AI to reinvent tomorrow before helping the business execute better today.
That distinction matters now. Tariffs, energy volatility, and supply shocks are changing customer economics faster than annual price lists can follow. At the same time, management teams are being asked to show a credible AI agenda.
For CEOs, Business Unit Presidents, and Private Equity Operating Partners, this is not primarily a technology question. It is an allocation question: where will the next euro of AI investment create measurable commercial value?
Call it Horizon 1: getting today’s price right before reinventing tomorrow’s model.
Most companies skip Horizon 1 — and pay for it
The conversation often jumps straight to subscriptions, outcome-based pricing, or a redesigned service model.
Meanwhile, the immediate pricing problem remains unresolved: the same increase is applied to customers facing completely different economics; long-tail accounts receive generic treatment; and sales teams cannot see which transaction context justifies a materially different recommendation.
The result is false progress: an ambitious monetization story atop the same broad segments, the same average assumptions, and the same sales uncertainty.
Key points include:
- AI connecting signals
- Changing the model when value changes
- Increasing value through continuity
Read the article, Most AI Monetization Strategies Start with the Wrong Question, on LinkedIn.