Wall Street is preparing for Nvidia’s earnings report, which could either revive the artificial intelligence trade or fuel further skepticism about its long-term potential. Analysts expect the chipmaker to report adjusted earnings of $2.09 per share on revenue of roughly $92 billion for its fiscal second quarter. That figure would represent a 96% increase from the same period last year.
Investors are closely examining AI spending trends.
The timing is significant. After a sharp selloff in July, chip stocks have failed to recover as questions persist about whether Big Tech’s heavy investments in AI will yield returns. Microsoft, Amazon, and Google recently eased some concerns with strong cloud growth, though scrutiny over capital expenditures has grown. Google and Meta, in particular, have faced pressure over their continued AI infrastructure spending.
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Nvidia remains central to this discussion. Its Data Center business is projected to bring in $85.4 billion in revenue this quarter, a 107% year-over-year increase. Hyperscalers like Amazon, Google, and Microsoft are expected to account for $43.5 billion of that total, while sales to AI clouds, industrial, and enterprise customers could reach $41.7 billion. The company’s Edge Computing segment, which includes PC, gaming, robotics, and automotive operations, remains a smaller but still important revenue stream.
Dependence on a few large customers presents risks. The same hyperscalers driving Nvidia’s growth are also developing their own AI chips to reduce costs and reliance on external suppliers. Over time, these companies could emerge as competitors.
Nvidia is expanding beyond hardware sales. Earlier this month, it announced a partnership with BlackRock, Blackstone, KKR, Apollo Global Management, Brookfield, and Goldman Sachs to establish financing platforms aimed at mobilizing over $500 billion in third-party capital for AI infrastructure. The effort addresses one of the industry’s biggest challenges: the rising cost of building data centers.
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The company is also supporting SB Energy and OpenAI’s plans for an 8-gigawatt data center in Ohio, with potential financing of up to $150 billion. These steps indicate Nvidia aims to influence not just hardware but the financial and physical foundation of the AI expansion.
Attention remains on the financial results. If Nvidia’s revenue growth slows or its guidance falls short, it could suggest the AI trade is losing momentum. A strong report, however, might ease recent doubts—at least temporarily.
The broader implications are clear. Nvidia’s performance will gauge the health of the entire AI sector, where massive spending continues despite uncertain returns.