Companies like Oracle and Broadcom face market corrections as investors confront the difficult realities of the AI buildout. Lower-than-expected margins, data center delays, and high capital expenditures are injecting a dose of reality into the previously overhyped infrastructure trade.
Related Insights
Despite a massive contract with OpenAI, Oracle is pushing back data center completion dates due to labor and material shortages. This shows that the AI infrastructure boom is constrained by physical-world limitations, making hyper-aggressive timelines from tech giants challenging to execute in practice.
The massive investment in AI infrastructure could be a narrative designed to boost short-term valuations for tech giants, rather than a true long-term necessity. Cheaper, more efficient AI models (like inference) could render this debt-fueled build-out obsolete and financially crippling.
The massive capital rush into AI infrastructure mirrors past tech cycles where excess capacity was built, leading to unprofitable projects. While large tech firms can absorb losses, the standalone projects and their supplier ecosystems (power, materials) are at risk if anticipated demand doesn't materialize.
The massive spending on AI infrastructure may be a form of 'malinvestment,' similar to the telecom buildout during the dot-com boom. Rajan warns that while AI's promise is real, the transition from infrastructure creation to widespread, profitable use could be slow, creating a valuation gap and risk of a market correction.
The AI boom's sustainability is questionable due to the disparity between capital spent on computing and actual AI-generated revenue. OpenAI's plan to spend $1.4 trillion while earning ~$20 billion annually highlights a model dependent on future payoffs, making it vulnerable to shifts in investor sentiment.
Historical technology cycles suggest that the AI sector will almost certainly face a 'trough of disillusionment.' This occurs when massive capital expenditure fails to produce satisfactory short-term returns or adoption rates, leading to a market correction. The expert would be 'shocked' if this cycle avoided it.
Contrary to claims of an AI bubble, the market is demonstrating rationality by punishing companies like Oracle and Broadcom for failing to meet AI-related expectations. This selective valuation indicates a discerning market that rewards performance over hype, not an indiscriminate bubble where any 'AI' stock soars.
Oracle's stock is trading near the value of its remaining performance obligations ($523B RPO vs. $568B market cap). This suggests investors are heavily discounting the future profitability of its massive AI data center deals, questioning the long-term economics of being a commodity compute provider.
Companies like Oracle are facing investor anxiety due to an "AI CapEx hangover." They are spending billions to build data centers, but the significant time lag between this investment and generating revenue is causing concern. This period of high spending and delayed profit creates a risky financial situation for publicly traded cloud providers.
The AI infrastructure boom is a potential house of cards. A single dollar of end-user revenue paid to a company like OpenAI can become $8 of "seeming revenue" as it cascades through the value chain to Microsoft, CoreWeave, and NVIDIA, supporting an unsustainable $100 of equity market value.
