A broad selloff across artificial intelligence-linked stocks on Tuesday has exposed a growing unease in markets that the pace of investment underpinning the AI boom may be running ahead of near-term demand.
The pullback followed a WSJ report that OpenAI has missed internal expectations for user growth and revenue, raising concerns about its ability to sustain the enormous financial commitments required to build and secure computing infrastructure. The reaction was swift and global, cutting across chipmakers, cloud providers, and investment vehicles tied to the AI supply chain.
Oracle, which has pledged up to $300 billion over five years to supply compute capacity to OpenAI, dropped 4%, underscoring how dependent parts of the ecosystem have become on a handful of large customers. Semiconductor firms Broadcom and Advanced Micro Devices fell 4% and 3%, while Nvidia eased more than 1%, a modest decline but notable given its central role in powering AI workloads.
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Elsewhere, CoreWeave, a leveraged cloud provider built around AI demand, slid more than 5%, reflecting heightened sensitivity among firms whose business models rely on sustained utilization of high-cost infrastructure. In Asia, SoftBank Group fell about 10%, highlighting the extent to which investor sentiment around OpenAI now reverberates across global capital markets. Qualcomm closed slightly lower after earlier gains tied to reports of collaboration with OpenAI on smartphone chips.
The market’s concern is being buoyed by a structural tension that has been building for months. The current AI cycle is defined by unprecedented upfront capital expenditure, with technology companies collectively expected to commit hundreds of billions of dollars annually to data centers, specialized chips, and energy infrastructure. Unlike previous software cycles, where marginal costs declined as products scaled, generative AI imposes recurring, high operating costs tied directly to usage.
According to the report, OpenAI’s finance chief, Sarah Friar, warned internally that if revenue growth does not accelerate, the company could face difficulty funding future compute agreements. That possibility introduces risk not just for OpenAI but for the broader network of suppliers that have expanded capacity on the assumption of continued exponential demand.
OpenAI rejected the report, stating: “This is ridiculous. We are totally aligned on buying as much compute as we can and working hard on it together every day.”
Oracle also sought to reassure investors, saying: “We’re incredibly excited about our partnership with OpenAI and remain focused on building and delivering the capacity they need to support rapidly growing demand. OpenAI’s new 5.5 model is a significant step forward, and we expect continued momentum as access to their technology expands across cloud providers.”
Even so, the episode has revived a question that has periodically surfaced during the rally: whether demand visibility justifies the scale and speed of investment. OpenAI’s recent $122 billion funding round, which valued the company at $852 billion, suggests that investors remain willing to underwrite that expansion. Yet the same scale amplifies scrutiny. When a company at the center of the ecosystem shows signs of uneven growth, the implications extend far beyond its own balance sheet.
Some analysts argue the market reaction may be overstated. Jordan Klein of Mizuho wrote: “You would assume any slowing was known by the investors, right? If not, shame on OpenAI. How new could update be as the round closed end March when the quarter would have ended. And it’s not even May 1. I highly doubt OpenAI fundamentals slowed that fast in under 30 days.”
His point indicates that a broader view is that the current volatility may reflect sentiment shifts rather than a fundamental break in demand.
Others see the development as part of a more gradual rebalancing. John Belton of Gabelli Funds said: “OpenAI’s growth seems to have slowed in late-2025 into early-2026 as the business ceded some share to Anthropic and Gemini. There is nothing here that suggests this is an issue for the pace of spending across the sector as a whole.”
The rise of Anthropic and the growing adoption of models from Google indicate that enterprise customers are increasingly pursuing multi-vendor strategies, diluting the dominance of any single provider while sustaining aggregate demand.
Still, the fragmentation of the market complicates forecasting. Companies building infrastructure must commit capital years in advance, often without precise visibility into how demand will be distributed among competing platforms. That uncertainty increases the risk of both overcapacity and underutilization, particularly if growth proves uneven across providers.
Luke Rahbari, CEO of Equity Armor Investments, cautioned against overinterpreting near-term metrics.
“OpenAI missing its revenue targets is, in the grand scheme, a distraction. In the current AI landscape, these projections are largely arbitrary. No major player in this race can accurately forecast their revenue or capital expenditure within a 25% to 50% margin of error,” he said.
His assessment captures a defining feature of the current cycle: scale is being built ahead of clarity.
The selloff, then, appears less like a reversal of the AI trade and more like a repricing of risk. Investors are beginning to distinguish between companies with demonstrable demand and those whose valuations rely heavily on projected growth curves. The underlying thesis of the AI boom, rising demand for compute, data, and automation, remains intact. What is shifting is the market’s tolerance for uncertainty in how, and how quickly, that demand translates into revenue.