In the current AI-driven market frenzy, investors are most concerned with one question: What is the true value of AI, and has the market already overpriced it?

Goldman Sachs' macro strategy team, in their latest report, sidestepped individual company prospects and instead took a macroeconomic top-down approach. Through a "simple arithmetic calculation," they issued a warning: The U.S. stock market may have already priced in most of AI's potential gains.

The research shows that AI-related companies have seen their market capitalization surge by over $19 trillion since the launch of ChatGPT, reaching—or even surpassing—Goldman Sachs' baseline estimate of AI's future capital income present value (approximately $8 trillion).

This suggests market pricing has significantly outpaced macroeconomic realities, and investors should be wary of overvaluation risks—especially if economic conditions or the AI investment boom take a turn.

**The "Ceiling" of Macro Gains: $8 Trillion** The report first set aside individual stock valuations to estimate AI's potential total contribution to the U.S. economy. Based on prior projections that AI would boost productivity by 1.5 percentage points over a decade, Goldman Sachs economists calculated a baseline present discounted value (PDV) of future capital income at around $8 trillion, with a reasonable range between $5 trillion and $19 trillion.

Goldman Sachs noted that if labor isn’t permanently displaced and profit shares in the economy remain stable, corporate earnings could permanently rise by about 15% after the transition period. Stock market growth should equal the discounted value of these additional profits, though the increase would be less than the 15% long-term rise in GDP and earnings due to the transition phase.

**$19 Trillion—Market Valuations Have "Far Outpaced"** The problem? Market pricing has already exceeded macroeconomic fundamentals. The report pointedly observed that since ChatGPT's release, just two categories—semiconductors and AI model developers—have seen their market cap grow by over $8 trillion, matching Goldman’s baseline estimate for AI's total potential capital gains. Expanding the scope to all AI-related listed companies, the total market cap increase reaches a staggering $19 trillion.

Goldman Sachs stated: > "These simple calculations suggest the market may have already front-loaded the vast majority of AI's potential value, concentrated in companies directly involved in or adjacent to the AI boom. Market pricing has raced far ahead of macroeconomic impact."

**Not Yet a Bubble, but Caution Advised** Goldman Sachs clarified that while valuations are elevated, they haven’t reached bubble territory. The macro perspective reveals systemic risks of potential overpricing—even if individual company valuations seem reasonable, the aggregate may not be, as even massive productivity gains have an upper limit in boosting overall economic profits.

The report also warned investors against two common cognitive fallacies: 1. **"Fallacy of Composition"**: Mistakenly assuming many companies can be big winners, leading to unrealistic total profit expectations. 2. **"Extrapolation Fallacy"**: Treating early-stage supernormal profit growth as sustainable while ignoring competition’s eventual erosion of margins.

However, the research noted that even with substantial valuation gains already priced in, further increases aren’t impossible—this could still occur even if final gains land at the lower end of estimates. Past innovation-driven booms (e.g., the 1920s and 1990s) saw markets overpay for future profits despite genuine underlying innovation.

For investors, this means carefully assessing the risk-reward ratio of AI-related investments, particularly watching for early signals of economic cycle shifts or sustainability in the AI investment wave. In today’s high-valuation environment, any fundamental reversal could trigger a sharper-than-expected market correction.