The artificial intelligence market is experiencing a paradoxical moment: industry leaders — OpenAI and Anthropic — are showing impressive revenue and valuation growth, but their future directly depends on a factor they do not fully control. This concerns access to computing power, data center financing, and regulatory decisions. This is not just an operational cost — it is a fundamental structural risk for the entire business model.

Computing as the Currency of Growth

OpenAI openly admits: their revenue grows in sync with the available volume of computing. Over two years — from 2023 to 2025 — the company increased computing capacity from 0.2 GW to 1.9 GW, and annual recurring revenue soared from $2 billion to over $20 billion. The ChatGPT developer directly calls computing the most scarce resource in the AI industry. According to their logic, more infrastructure means faster deployment and monetization. Interestingly, the company has moved from a single provider to a "diversified ecosystem," hinting at attempts to reduce dependence, but this does not solve the shortage problem.

Anthropic is following the same path. In May 2026, they raised $65 billion in a Series H round at a $965 billion valuation, and their annual revenue exceeded $47 billion. The funds are directed toward expanding capacity for Claude. It is clear that both companies are playing by the rules of the "infrastructure race," where the one who scales faster survives.

The Cost of Infrastructure: Trillions of Dollars and Uncertainty

Scaling AI models is becoming a capital-intensive task not only for developers but also for the entire supply chain. Analysts at Goldman Sachs Research predict that the four largest hyperscalers — Meta, Microsoft, Amazon, and Alphabet — will spend $5.3 trillion on capital expenditures in 2025–2030. OpenAI and Anthropic are not included in this selection, but they are the ones creating demand for these capacities.

The Bank for International Settlements, in its 2026 annual report, warned of risks: the five largest cloud providers will spend over $1 trillion on AI infrastructure in 2025–2026. The problem is that these commitments already outpace the companies' profits and free cash flow. Competition for leadership could lead to excessive investments in projects with uncertain returns. If monetization does not meet expectations, a sharp reduction in funding will follow, hitting the entire sector.

Regulatory Risk: When Government Becomes Part of the Infrastructure

Beyond the cost of computing, major AI companies face sudden restrictions from authorities. In June, Anthropic had to halt access to the Fable 5 and Mythos 5 models due to a directive from the U.S. government under export controls. Notably, the authorities' letter contained no specific details about the security issue, and the complaints were related to a possible bypass of protective mechanisms.

In the same month, the Donald Trump administration asked OpenAI not to release GPT-5.6 to the general public immediately due to security concerns. The company was forced to first provide the model to a limited number of clients. On June 30, the Department of Commerce lifted the restrictions, but the episode showed how vulnerable AI leaders are to political will.

Anthropic's relationship with authorities is particularly tense. In February 2026, the U.S. Army used Claude in an operation to capture Venezuelan President Nicolas Maduro, and the Pentagon chief called the developer a "supply chain risk." CEO Dario Amodei stated that the company would prefer not to cooperate with the Pentagon rather than agree to the use of technology that could "undermine democratic values." This conflict creates an additional layer of uncertainty for investors.

Going Public: A Bet on Sustainability

Despite all the risks, both companies continue to prepare for the public market. OpenAI filed a confidential IPO application on June 8, Anthropic a week earlier. The placement parameters are not defined, but the key question for investors will not be valuation, but the economics of scaling: how much does it cost to sustain user growth, how quickly do data centers pay off, how stable are funding channels, and can a regulator restrict access to the flagship product.

My Conclusion

OpenAI and Anthropic have found themselves in a trap of their own success. Their business model requires colossal capital investments that outpace current monetization. At the same time, regulatory risks add unpredictability. The market seems willing to pay for the future, but the question is how long investors will tolerate uncertainty. If at least one of these factors — access to computing or regulatory pressure — spirals out of control, we could see a sharp correction in valuations across the entire AI sector.