AI Disruption Reshapes US Equity Valuations as Terminal Value Volatility Takes Center Stage

The narrative of artificial intelligence disruption is reshaping the logic behind US equity pricing. Goldman Sachs’ latest research highlights that investor concerns about AI’s potential to erode long‑term profitability have shifted attention to the most sensitive and least quantifiable component of valuation — terminal value, which represents profit expectations beyond a ten‑year horizon.

Goldman Sachs estimated in its April 27 report that approximately 75% of the S&P 500’s current equity value is derived from terminal value, a level near a 25‑year high and reminiscent of the optimism seen during the internet bubble. The bank calculated that a one‑percentage‑point reduction in assumed long‑term growth would reduce enterprise value across the S&P 500 by about 15%, with high‑growth stocks facing declines as steep as 29%. Goldman noted that debate over AI disruption and the resulting terminal‑value uncertainty is likely to persist for several quarters, with disruption risks exerting pressure until AI applications reach maturity.

Terminal value’s elevated share reflects market optimism but also heightens sensitivity to growth assumptions. Goldman’s adjusted 10‑year dividend discount model shows terminal value accounting for roughly 84% of enterprise value in high‑growth stocks, about 72% for the S&P 500 overall, and around 59% for low‑growth names. This mirrors conditions during the internet bubble, when long‑term growth expectations drove valuations to extremes.

The software sector has been at the epicenter of repricing. Concerns that AI tools could lower barriers to entry and enable low‑cost competition have driven the S&P 500 Software and Services index down about 17% year‑to‑date, while a basket of software stocks has fallen 19%. Selling pressure has spread to other asset‑light industries, even as near‑term earnings expectations remain resilient. This divergence underscores that the market is repricing long‑term growth prospects rather than reacting to short‑term fundamentals.

Goldman’s empirical analysis shows that implied long‑term growth expectations are the most important determinant of valuation multiples across companies. A one‑standard‑deviation increase in implied long‑term growth corresponds to a 0.6 standard‑deviation rise in forward P/E, equivalent to about four P/E points. This influence is roughly three times greater than that of recent earnings growth, balance‑sheet strength, market capitalization, or earnings stability. In contrast, short‑term valuation changes are more strongly explained by near‑term growth expectations and risk premia. Since 1990, Goldman finds that near‑term expectations have explained about three times as much of quarterly multiple variation as long‑term expectations, reflecting the slower adjustment of long‑term forecasts.

This structural dynamic means that if AI disruption narratives undermine confidence in long‑term growth, the valuation impact could be profound and difficult to reverse.

Goldman advises corporate managements to respond proactively to rising terminal‑value uncertainty. The report emphasizes the need for stronger communication of long‑term growth plans, yet only 5% of S&P 500 companies discussed financial metrics beyond five years in recent earnings calls, primarily in utilities and real estate. Goldman recommends that management teams provide more guidance on addressable market size, growth trajectories, and profitability outlooks, even if multi‑year forecasts carry uncertainty.

The bank also suggests that accelerated share‑repurchase programs (ASRs) can serve as confidence signals. Academic studies show ASR announcements typically generate stronger positive price reactions than ordinary buybacks. Goldman cautions, however, that large repurchases may be misinterpreted as a lack of growth opportunities. To avoid mixed signals, managements should combine ASR programs with clear statements of optimism about future growth prospects.