Torsten Slok at Apollo published a chart last week that is easy to dismiss because it looks too neat. Silicon and equipment sit at a 41% operating margin. Models and applications sit at -59%. Compute and cloud, energy and grid, and the rest of the stack sit between them. Fortune turned the point into a clean headline about AI profits being funded by investors rather than customers.
The chart deserves a slower read. In a normal software story, the layer closest to the customer should have the best chance at durable margin. It owns distribution, usage data, switching costs, and pricing power. The infrastructure suppliers get paid, but the product layer keeps the surplus if the end market is real.
AI is currently paying out in the other direction. The farther a company is from the end user, the cleaner the margin often looks. Nvidia, memory suppliers, equipment vendors, and parts of the power stack are receiving cash from the buildout now. The model and application layer is still trying to prove that end customers will pay enough, often enough, at a gross margin high enough to justify the infrastructure already being ordered.
Start with the steelman for the bulls. Early general-purpose technologies often look wasteful before the applications catch up. Railways, fiber, cloud, and smartphones all had periods where infrastructure arrived ahead of obvious demand. A narrow customer-ROI screen can miss the option value of building capacity before the use cases are fully priced. Goldman Sachs Research now estimates global AI-related investment above $1 trillion in 2026 and argues that the level as a share of GDP still sits inside the historical range for prior technology buildouts. The near-term indicators it tracks also do not show an imminent capex slowdown.
