Bottom line: Foundation models are turning into interchangeable raw materials, with real economic gains shifting toward specialized model adaptation and intelligent product integration.
AI labs can currently still set prices for foundation models autonomously, but the market shows signs of a development that will degrade language models to interchangeable infrastructure components. Actual economic value creation will increasingly no longer occur at the model level itself.
The market for large language models currently exhibits asymmetric pricing power: OpenAI, Anthropic, Google and other AI labs largely set the costs for API access and model usage independently. This position enables high margins and allows companies to offset infrastructure costs through pricing power.
However, long-term market developments point in a different direction. Once multiple competitive models are available on the market and technical differences between them diminish, competition will primarily be conducted through availability, reliability and cost-efficiency. This leads to commoditization: foundation models become expected-to-be-present infrastructure whose prices continuously decline.
For CDOs and decision-makers, this means a reassessment of AI investment strategy. True value creation is shifting in two directions: on one hand toward specialized, domain- or industry-specific models and fine-tuning, on the other toward the application layer—that is, the ability to effectively deploy AI capabilities in products and processes. Companies relying solely on standard models compete in a category with shrinking margins.
Source: www.golem.de · Published 14 July 2026
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