It seems that OpenAI failed to meet some of the internally set benchmarks for the number of active ChatGPT users and other key metrics related to the company’s revenues. This update has reignited discussions about OpenAI’s financial strategy, particularly amid commitments to sizable compute contracts.
As stated by The Wall Street Journal, CFO Sarah Friar has expressed worries about whether the organization will be able to sustain the multi-billion investments into computing power. This does not seem like a minor gamble. In order to justify such compute investments, there has to be steady growth.
Both Sam Altman and Sarah Friar made their position clear. As part of a statement issued jointly, they stressed that they were totally dedicated to purchasing as much computing power as they could. Again, the rationale was simple the more computing power they acquire, the more users and revenues they will get.
OpenAI’s Multi-Billion Dollar Surge vs. Market Skepticism
Investor sentiment has started to shift. While OpenAI recently raised about $122 billion—well above its $100 billion target—some analysts now question how long that momentum can last. One estimate suggests the company could run low on cash by mid-2027 if funding slows and expenses stay high.
The market reaction has been quick. Stocks tied to the AI ecosystem saw declines after the news spread. Nvidia dropped about 1%, while AMD fell 4%. Oracle and CoreWeave each slid around 5%. In Japan, SoftBank closed nearly 10% lower on the Nikkei 225, making it one of the worst performers that day.
One company has stayed relatively stable: Microsoft. Its position looks different. Even after ending its cloud exclusivity agreement with OpenAI, Microsoft still holds a 27% stake in OpenAI’s for-profit arm. It has also invested heavily over time, which may give investors more confidence in its exposure.
At the same time, competition has grown stronger. OpenAI helped spark the large language model race when it launched ChatGPT in late 2022. Since then, rivals have closed the gap. Anthropic has gained traction with its Claude models, especially among developers and enterprise users. Google has also pushed forward with its Gemini models, which now outperform ChatGPT in several benchmarks.
Altman has acknowledged this pressure. Reports say he issued a “Code Red” warning internally last year as competition intensified. That response highlights a key challenge: OpenAI must scale fast while keeping its lead in performance and usability.
The $400 Billion Infrastructure Bet of OpenAI
Despite the concerns, the company continues to double down on infrastructure. It has signed major deals to secure future compute power. One agreement includes a 4.5-gigawatt contract with Oracle, valued at around $300 billion. Another partnership aims to deliver 10 gigawatts of Nvidia hardware to data centers, with a price tag near $100 billion.
These are massive commitments. They reflect a belief that demand for AI will keep rising at a sharp pace. OpenAI argues that limited compute capacity, not lack of interest, has slowed its growth so far.
Not everyone agrees. Dario Amodei has warned that some companies may be pushing infrastructure spending too far. From his view, careful scaling matters more than rapid expansion. OpenAI, however, sees it differently. In a memo to investors, the company said that earlier caution across the industry may have underestimated how fast demand would grow.
That claim now faces a real test. If demand keeps rising, OpenAI’s strategy could pay off. More compute could unlock better models, faster responses, and wider adoption. But if growth slows, the cost of those contracts could weigh heavily on its balance sheet.
For now, the situation remains fluid. OpenAI still holds a strong position in the AI market, backed by major partners and deep funding. Yet the gap between expectation and performance has started to draw attention.
The next phase will depend on execution. The company needs to grow its user base, improve monetization, and manage its spending at the same time. That balance will decide whether its bold bets on compute turn into long-term strength or financial strain.
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