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Goldman Sachs: AI Trading Bubble Concerns Are Premature, Current Market Driven by Earnings

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On July 2, Goldman Sachs stated that investors should not prematurely exit the AI sector. Despite significant gains in AI-related stocks this year and rising concerns about a bubble, Ben Snider, head of U.S. equity strategy at Goldman Sachs, indicated that the current market resembles an earnings-driven bull market rather than a speculative frenzy solely reliant on valuation expansion. Snider believes that AI investment opportunities are still concentrated in three main areas: AI infrastructure, power infrastructure, and recently underperforming cloud providers and large-scale platforms. The first area includes semiconductors, servers, AI networking equipment, and data center hardware; the second encompasses power equipment, utilities, and energy infrastructure that support data center expansion; and the third includes major platform companies such as Amazon, Microsoft, Meta, Alphabet, Oracle, and IBM. Goldman Sachs' core argument is that while many AI infrastructure stocks have surged, their valuations have not detached from earnings expectations in the manner typical of a bubble. Some stocks related to storage, semiconductors, and data centers still reflect market skepticism rather than unanimous optimism. In other words, investors are still demanding that these companies prove that AI capital expenditures can translate into profits through orders, margins, and cash flow. Goldman Sachs does not recommend indiscriminately buying all AI concept stocks, but rather continues to bet on those companies that can directly generate revenue and profit growth from AI capital expenditures. They believe that AI trading has not yet entered a phase of 'storytelling without regard to profits.' As long as earnings continue to be revised upward, AI infrastructure may remain one of the most important themes in the U.S. stock market.
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