More and more clients are asking Goldman Sachs: Is the US stock market "too optimistic"? What is the next step for "AI trading"?
Goldman Sachs believes that while the current AI-driven market is highly valued, it has not yet reached the level of irrational bubble, maintaining an overall cautiously optimistic tone. However, it also warns that the market's euphoria is highly dependent on the capital expenditures of tech giants. If this "infrastructure boom" slows down in the future, it will put pressure on valuations, and in extreme cases, could even lead to a 15-20% correction in the U.S. stock market. Whether the market can successfully transition from the infrastructure phase to the profitability phase is key to determining future trends
"Are we being too optimistic?" This is the question that Goldman Sachs strategists have heard most frequently from clients recently.
Indeed, the market's concerns are not without reason. According to reports from the Wind Trading Desk, Goldman Sachs' latest report shows that after a 32% surge in 2024, AI-driven related stocks have risen another 17% so far in 2025. With such a rapid increase, the expected price-to-earnings ratio of the S&P 500 index has reached 22 times, placing it at a historically high 96th percentile.
However, after in-depth analysis, Goldman Sachs provided a relatively moderate answer: optimistic, but not yet irrational.
The report pointed out that the long-term earnings growth expectations implied by current market prices are about 10%, which is slightly above the historical average of 9%, but far below the 16% during the 2000 tech bubble and 13% at the market peak in 2021.
Even the most dazzling "star stocks" in the market—large tech stocks—have relatively restrained valuations. The report shows that the average expected price-to-earnings ratio of the top five tech giants (Nvidia, Microsoft, Apple, Google, Amazon) is 28 times, significantly lower than the peak of 40 times in 2021 and 50 times during the tech bubble. Goldman Sachs believes that compared to the two major peaks in history, the current valuations, while expensive, still have some distance to go.
The "Midfield Battle" of AI Trading: Infrastructure Frenzy and Growth Bottlenecks
Goldman Sachs divides the evolution of AI trading into different phases, and the current market is clearly still immersed in the "second phase"—the frenzy of infrastructure construction.
The fuel for this frenzy comes from the hundreds of billions of dollars in capital expenditures by major cloud service providers such as Amazon, Google, Meta, and Microsoft. Goldman Sachs' report cites data showing that the market's forecast for these giants' total capital expenditures in 2025 has been raised by $100 billion just this year, reaching $368 billion.
This massive investment directly translates into orders and profits for infrastructure suppliers such as semiconductors, power equipment, and technology hardware, driving their stock prices to soar.
However, beneath the feast lies hidden risks. Goldman Sachs warns that the rapid growth of capital expenditures "will inevitably slow down," posing risks to the valuations of "second phase" stocks. Currently, the stock price increases of these companies have far exceeded their recent earnings growth trajectory, reflecting the market's extremely optimistic expectations for their future growth.
Key Risk: Slowdown in Capital Expenditures Could Trigger a 15-20% Correction
Goldman Sachs clearly pointed out the current core weakness of AI trading: dependence on the capital expenditures of tech giants. Analysts generally predict that the growth rate of capital expenditures will show a significant slowdown in the fourth quarter of 2025 and into 2026. Once the inflection point in growth appears, it could put pressure on the valuations of related stocks.
Although predicting the timing of this inflection point is extremely challenging—because market consensus has repeatedly underestimated the investment scale of tech giants—this trend of slowdown is "inevitable."
The firm constructed an extreme stress test scenario: if the capital expenditures of tech giants suddenly revert to 2022 levels, this would reduce the expected sales growth of the S&P 500 index by about 30% in 2026The macro valuation model report shows that this shock will not only directly hit short-term revenue but will also severely damage the market's confidence in long-term AI-driven profit growth, potentially leading to a 15% to 20% reduction in the valuation multiple of the S&P 500 index.
Where to go next? The market is still waiting for the "profit story"
As the boom in infrastructure construction gradually peaks, can the next stop of AI trading—"Phase Three," which involves companies achieving revenue growth through AI empowerment—take over?
Goldman Sachs' observations reveal the market's hesitation. The report states that investors show "limited interest" in companies of the "Third Phase," especially in the software industry.
The reason lies in the market's struggle to answer a complex question: for many software and service companies, is AI a catalyst for growth or a disruptive threat? Goldman Sachs analysts point out that investors are concerned that AI may disrupt existing pricing models and lower industry entry barriers, thereby compressing the profit margins of existing software giants.
Unlike the clear winners in "Phase Two," "Phase Three" will see significant differentiation, with both winners and losers. As a result, investors have become particularly selective. The report emphasizes that the market may require seeing a "real and tangible" impact of AI on these companies' recent profits before truly embracing them.
As for the longer-term "Phase Four"—AI-driven productivity enhancement, Goldman Sachs believes this is still just the beginning. The report cites data showing that although 58% of S&P 500 companies have mentioned AI in their earnings calls, primarily applied in customer support, programming, and marketing, few companies can quantify AI's specific contribution to current profits.
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