Built to compensate for people
Almost every information system is designed around one assumption: a human has to operate it. As a result the system has to compensate continuously. For different frames of reference, for varying skills, for typos, for preferences, and for the departure of employees who take their knowledge with them. That compensation layer is not a detail, it is the bulk of the complexity.
The price of that compensation
The result is predictable. Conventional systems are expensive, slow, volatile and complex. A large part of the IT budget goes to keeping that compensation layer alive: licences, implementations, training, support and endless adjustments with every reorganisation.
The most expensive systems are not the ones you buy, but the habits they force on you.
The inflection: processing costs next to nothing
Something fundamental has changed. The cost of automated information processing has dropped to a fraction of the human equivalent. A task that costs a knowledge worker tens of euros an hour is done by an AI model for cents. With that, the reason for the compensation layer disappears.
What AI-native really means
Working AI-native is not bolting AI on top of your existing systems. It is relaying the foundation: restructuring your information so AI can work on it reliably, a modular AI stack that grows with every model generation, and custom software you own yourself. No subscription, no dependency.
The hidden cost does not disappear on its own. But for the first time, it has become optional.