Is the market overestimating AI? Goldman Sachs macro team offers a "simple calculation"

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Author: Zhao Ying

Source: Hard AI

In the current AI-driven market frenzy, the questions investors care about most are: What is the true value of AI? Has the market already overvalued it?

In its latest report, Goldman Sachs’ Macro Strategy Team does not dwell on the prospects of individual companies. Instead, taking a top-down macroeconomic view, they offer a warning through a “simple arithmetic calculation”: the U.S. stock market may have already priced in most of the potential gains brought by artificial intelligence in advance.

Research shows that since the launch of ChatGPT, the market capitalization of AI-related companies has soared by over $19 trillion, already reaching or even surpassing Goldman Sachs’ benchmark estimate of AI’s future present value of capital returns (roughly $8 trillion).

This means that market pricing has far outpaced the actual impact on the macroeconomy. Investors need to beware of the risk of overvaluation, especially if there is a turning point in the economy or the current AI investment boom.

The "Ceiling" of macroeconomic returns — $8 trillion

The report first sets aside the valuation of individual stocks, and attempts to calculate the total returns AI could potentially bring to the entire U.S. economy. Based on their previous estimate that AI will boost productivity by 1.5 percentage points over ten years, Goldman Sachs’ economists estimate the future capital income "present discounted value" (PDV) at about $8 trillion, with a reasonable range between $5 trillion and $19 trillion.

Goldman Sachs states that if the workforce is not permanently replaced, and the share of profits in the economy remains stable, then corporate profitability will also increase permanently by about 15% after the transition period. Growth in stock market value should equal the discounted value of these additional profits. Due to the transition period, this increase will be less than the 15% rise in GDP and long-term profits.

$19 trillion — Market valuations are “far ahead”

The issue is that market pricing has already outstripped macro fundamentals. The report sharply points out that, since the release of ChatGPT, the market capitalization increase of just the semiconductor and AI model development companies exceeds $8 trillion, which matches Goldman Sachs’ benchmark prediction for potential total returns from AI. Expanding the scope to all publicly listed AI-related companies, the value added reaches $19 trillion.

Goldman Sachs states:

These simple calculations suggest that the market may have already priced in the vast majority of AI’s potential value in advance, and that this value is concentrated primarily among companies directly participating in or close to the AI boom. ... Market pricing is now far ahead of the macroeconomic impact.

Not at bubble levels yet—Cautious but not panicked

Goldman Sachs notes that while company valuations are high, they have not yet reached bubble territory. The macro perspective reveals that there is potential systemic risk from overpricing: even if individual company valuations appear reasonable, the aggregate may not be—since even massive increases in productivity have an upper limit on overall economic profit growth.

The report also warns investors about two common cognitive biases:

The first is the “aggregation fallacy,” i.e., the mistaken belief that many companies can all be big winners, leading to unrealistic expectations for total profits;

The second is the “extrapolation fallacy,” i.e., treating the initial excess profit growth from innovation as normal, and overlooking the law that competition will eventually erode profits.

However, the research also notes that even if a significant portion of value gains has already been priced in, this doesn’t mean that more can’t be added. Even if eventual returns fall at the lower end of the estimates, this is still possible. Past innovation-driven boom eras—such as the 1920s and 1990s—saw the market pay excessively high prices for future profits, even when fundamental innovation was real.

For investors, this means it is necessary to more cautiously assess the risk-reward ratio for AI-related investments, and to pay close attention to early signs of changes in the economic cycle or the sustainability of the AI investment boom. In the current high-valuation environment, if there is a shift in fundamentals, the extent of market correction could exceed expectations.

This article is from WeChat Official Account "Hard AI". For more cutting-edge AI news, please click here

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