Major technology companies are significantly increasing capital expenditures to fuel AI development, leading to concerns about a potential market correction. Meta's second-quarter capital expenditures reached $31.08 billion, a substantial increase from $17.01 billion a year earlier. The company also raised its 2026 capital-spending forecast to a range of $130 billion to $145 billion. Despite a 28% increase in revenue to $60.8 billion, Meta's operating income declined 8%, and free cash flow dropped to $784 million due to this increased spending.
Alphabet also saw a significant surge in capital expenditures, spending $44.9 billion during the second quarter, primarily on servers, data centers, and networking equipment. Google Cloud revenue rose 82% to $24.8 billion, with operating profit more than tripling to $8.8 billion. Alphabet's cloud backlog also grew to $514 billion, an increase of over $50 billion from the previous quarter. Amazon's AWS cloud unit generated $42.2 billion in second-quarter sales, up 37%, and its operating profit increased 64% to $16 billion. Amazon's trailing 12-month purchases of property and equipment increased by $66.1 billion, largely driven by AI infrastructure.
Microsoft reported quarterly revenue of $90 billion, an 18% year-over-year increase. Azure and other cloud-services revenue jumped 43%, contributing to a total Microsoft Cloud revenue of $59.3 billion, up 27%. Azure's annual revenue surpassed $100 billion for the first time, and Microsoft's commercial remaining performance obligations increased 84% to $678 billion. Nvidia reported impressive fiscal first-quarter revenue of $81.6 billion, an 85% increase from the prior year, with data-center revenue alone rising 92% to $75.2 billion.
Despite these strong revenue figures, the massive capital outlays are raising red flags. Fitch Ratings identified an AI market correction as a major credit risk due to rising valuations, the scale of AI capital expenditure, and uncertain returns. SoftBank, a significant investor in OpenAI, is facing scrutiny over how it will fund its commitments, with $30 billion of obligations due in the second half of 2026 and increasing reliance on loans secured against its holdings. The iShares Semiconductor ETF, tracking major US-listed chip companies, fell 22.1% in July, and an index of 80 large semiconductor companies lost over $3 trillion in market value between early July and the low point of a recent selloff, indicating investor caution.
Analysts like David Gibson of MST Financial suggest that pressure on SoftBank, Arm, and memory stocks will continue until end-users and corporations demonstrate a productivity surge from AI. Concerns are also mounting regarding OpenAI's valuation, with reports of a potential $1 trillion IPO valuation facing skepticism, as some analysts believe its true value might be closer to $300 billion, given competition from cheaper Chinese AI models. This intense spending and valuation uncertainty suggest that the market is reassessing the assumptions behind the AI buildout, including how quickly current capital expenditure will generate returns and how it is being financed.
