OpenAI falls short of internal growth targets, market erases tens of billions

OpenAI is trying to project confidence following reports that the company failed to meet internal targets for revenue and audience growth. But on April 28, 2026, the market reacted harshly: investors began dumping shares of companies whose AI bets are directly tied to OpenAI's success.

Which targets were missed

According to The Wall Street Journal, OpenAI failed to reach its internal target of 1 billion weekly ChatGPT users by the end of 2025. By February 2026, the service had reached 900 million weekly active users — still a colossal scale and growth of roughly 125% year-over-year. But the problem is that for OpenAI, such a result is considered not simply good or bad, but sufficient or insufficient to service its massive compute infrastructure obligations.

The journal also reported that in early 2026, OpenAI missed its own monthly revenue targets several times. In the consumer market, it faces pressure from Gemini, while in coding and the enterprise segment, Anthropic is increasingly taking market share.

According to the report, OpenAI's annual run rate is currently around $25 billion, while Anthropic reached approximately $30 billion in April. For a company that essentially set the pace for the entire generative AI market, this is more than just a slowdown — it's a loss of revenue leadership.

Why the market is nervous

The investor reaction was not about one news cycle or a weak quarter. The market began recalculating the entire chain of bets built around a scenario in which OpenAI grows almost without disruption, quickly monetizes demand for its models, and turns this growth into a guaranteed stream of orders for cloud providers, chip makers, and infrastructure contractors. When a crack appears in this narrative, the revaluation instantly ripples across the entire connected ecosystem.

• Oracle lost 7.7% after the market recalled its massive compute bet on OpenAI
• CoreWeave fell 7.4% amid its dependence on infrastructure contracts with OpenAI
• SoftBank dropped nearly 10% in Tokyo following its commitment of around $60 billion in OpenAI funding
• Nvidia, Broadcom, AMD, and Arm declined 2–6%, as their AI demand is also tied to the pace of ecosystem expansion

"This is clickbait of the highest order," an OpenAI representative said of the WSJ publication.

The problem for the company is that such rebuttals don't answer investors' main question. Nobody disputes that OpenAI's business is large, rapidly growing, and still one of the strongest in the industry. The dispute is over something else: can this growth support tens and hundreds of billions of dollars in contractual obligations if competitors are already eating into its share, and its own CFO is warning about financing risks and the possibility that the company may not be ready for a public offering?

The price of ambitions

The key figure now is around $600 billion in compute infrastructure commitments through 2030. Previously, the company had estimated needs even higher, but even after the revision, the bar remains extreme. This money must be paid back not with promises, but with revenue.

According to the report, CFO Sarah Friar warned colleagues: if growth doesn't accelerate, OpenAI could face difficulties in financing future compute agreements. The publication also mentioned another painful point: the organization may not be ready for an IPO in the fourth quarter of 2026.

OpenAI does have defenses. More than 40% of its revenue already comes from the enterprise segment, the number of paying business users has grown to 9 million, and the advertising business, launched in February, surpassed $100 million in annual revenue within six weeks. Plus, the company has 50 million paying subscribers.

In other words, the problem is not that OpenAI is weak. The problem is that given the current valuation and scope of infrastructure commitments, it needs to be not just strong, but historically exceptional in terms of growth rate and monetization quality.

What this means

The OpenAI story shows that the AI market is entering a new phase where flashy releases and record-breaking funding rounds are no longer enough. Investors are starting to look not only at model quality, but also at business mathematics: how much scale costs, who actually captures the revenue, and whether infrastructure bets will withstand competitive pressure. For OpenAI, this is a moment when it must prove not leadership in hype, but economic sustainability.