The big AI companies are going to see their margins disappear

"That opportunity exists in the AI training and inference business. But perhaps not for long. Two leading American AI companies, Anthropic and OpenAI, are not actually profitable at this point, but their pitch to investors is something along the lines of "just hang in there a few more years and keep sending cash.""

"Given reports that Claude Code subscribers paying $200 a month can potentially consume $5,000 worth of tokens and that OpenAI is also losing money on subscriptions, it starts to become a bit clear why Anthropic, OpenAI, Google, and Microsoft have already started pushing customers toward metered usage pricing. AI revenue needs to go up for frontier model makers to survive. And then AI adoption needs to grow."

"Government agencies and large corporations that don't keep a close eye on fees may be terrified enough of AI-enabled exploitation to pay a premium for models like Anthropic's Mythos and OpenAI's GPT-5.5. But more price-sensitive folk may shop for cheaper tokens. And they're likely to find them."

"Benedict Evans, among the more astute industry observers, expects AI models will be commoditized. In his recently updated presentation, " AI eats the world," he suggests that the AI supply/demand imbalance will ease and the pricing power of leading AI labs will dissipate. He argues that models will become commodity infrastructure and that innovation and pricing power will have to move up the stack."

AI training and inference businesses face profitability pressure as major frontier model providers remain unprofitable while relying on continued investor funding. Subscription pricing can lead to heavy token consumption, creating incentives to move customers toward metered usage pricing. Higher-paying customers may accept premium models due to perceived risk of AI-enabled exploitation, while price-sensitive customers will seek cheaper token options. Industry expectations point to commoditization of AI models as supply and demand balance improves, reducing pricing power for leading labs. Innovation and pricing power are expected to shift to higher layers, including developer tools and services built on top of base models.

Read at theregister