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NewsMaterial3 min readDisconfirmAI Editorial

American Century Investments Co-Chief Investment Officer: AI Capital Expenditure Resembles Cloud Computing Investment from Two Decades Ago, Not the Dot-Com Bubble

Keith Lee, Co-Chief Investment Officer of Global Growth Equity at American Century Investments, explains that long-duration risk and rising debt financing costs for AI have jointly depressed growth stock valuations. However, he believes the long-term economic return path of current AI capital expenditure is similar to Amazon, Microsoft, and Alphabet's construction of cloud infrastructure in the past, rather than the overinvestment seen during the dot-com bubble.

Verified 2026-11-12 07:19 GMT+8

In an analysis released in October 2026, Keith Lee, Co-Chief Investment Officer of Global Growth Equity at American Century Investments, and Ryan Walker, Client Portfolio Manager, attempted to answer a question confusing the market: Why have growth stocks with strong earnings growth experienced severe volatility?

Their explanation begins with the duration mechanism. The value of growth stocks comes primarily from future earnings; when long-term interest rates rise, investors increase the discount applied to distant cash flows, making these long-duration assets the first to suffer. The article points out that yields on U.S. long-term Treasury bonds recently reached their highest level since 2002, driven by three factors: U.S. federal debt surpassed $40 trillion in mid-August; inflation has remained above the Federal Reserve's target for five consecutive years; and in September 2026, the Federal Reserve raised interest rates under the leadership of new Fed Chair Kevin Warsh.

The impact of rising interest rates on AI investment is twofold. On one hand, higher discount rates directly depress growth stock valuations. On the other hand, a large amount of AI infrastructure investment relies on debt financing—estimated that the four largest AI cloud providers and Meta doubled their debt scale to $350 billion over the past five years, issuing approximately $121 billion in bonds alone last year. Rising interest rates mean increased financing costs for these projects, making it more difficult to achieve returns.

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However, the core argument of the two authors is not pessimistic. They explicitly state that they do not believe current AI investment is comparable to the excessive spending of the dot-com bubble period. They cite a historical analogy: twenty years ago, when Amazon, Microsoft, and Alphabet invested heavily in building cloud infrastructure, investors similarly worried whether these expenditures would generate returns. The authors point out that while these investments were costly and put pressure on current earnings through channels such as depreciation, they ultimately became key drivers of growth and earnings. The authors believe that current AI capital expenditure may create similar long-term benefits, because the demand for computing power required to run AI applications far exceeds the supply capacity of existing infrastructure.

But they also retain important qualifying conditions. Past success does not guarantee future results, and the returns on current AI investments remain uncertain. Not all companies will benefit equally from AI spending, and some investments may prove more successful than others. In the authors' view, companies with broad exposure to AI models, semiconductors, and cloud infrastructure may be in a more favorable position as AI applications continue to expand.

A notable market detail is that earnings growth itself has already improved valuations. S&P 500 earnings grew by more than 50% over the twelve months ending in June 2026, with Big Tech profits growing over 100% year-over-year, and the semiconductor industry nearing 140%. Earnings growth increased the denominator in the P/E ratio, and combined with weaker stock price performance, made growth stock valuations more attractive relative to their own history and even to value stocks. But the authors also acknowledge that the stock market focuses more on future earnings than past performance; analysts expect earnings growth of nearly 30% next year for large-cap S&P 500 stocks—whether this expectation can be realized is precisely the core tension behind the current volatility.

Sources

  • americancentury.com↗
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