According to financial data on OpenAI cited by The Information, the company loses roughly $1.22 for every $1 in revenue earned; it projects annual revenues of about $30 billion by 2026. Meanwhile, the Wall Street Journal reports that OpenAI has committed to spending approximately $600 billion on servers and data centers. In contrast, Apple’s direct capital expenditure on AI remains relatively stable. By entering into a fixed-fee partnership with OpenAI, Apple integrates ChatGPT into Apple Intelligence at minimal cost rather than developing its own large language models, thus reaping the benefits of cutting-edge AI capabilities without bearing hefty infrastructure expenses.
However, cracks have emerged in this arrangement. Reportedly, since ChatGPT integration within Apple Intelligence has generated far less revenue for OpenAI than anticipated, the company is considering legal action over contract terms. Apple’s strategy reflects a broader structural divergence within the AI industry: while a handful of ‘heavy-asset’ firms shoulder massive costs related to model development and computational infrastructure, partners able to access these resources affordably enjoy disproportionate commercial advantages. Earlier reports also highlight similar trends: Fortune noted Microsoft curtailing software licenses due to AI-powered coding tools driving up operational costs beyond employee salaries, while Goldman Sachs forecasts a 24-fold surge in token consumption by 2030 driven by AI agents. Collectively, these developments underscore how escalating AI-related expenditures are compelling industries to reassess the viability of existing business models.