Stock Slide Resurfaces as AI Construction Cost Rises

By the Editorial Team · Monday, October 19, 2026

AI stocks have shown heightened volatility as rising inflation raises borrowing costs, threatening the sustainability of heavy investment in data centers despite robust current profits. Analysts warn that the surge in capital expenditures may soon taper to maintenance spending, potentially slowing earnings growth and limiting long-term investor gains.

Artificial intelligence (AI) stocks have experienced significant volatility recently amid rising inflation, which has increased financing costs and cast doubt on the sustainability of debt-fueled investments in data centers. Investors are increasingly cautious about the potential for soaring capital expenditures to stall, despite the strong profits currently reported by many AI-related companies.

The rush to build out AI infrastructure has driven robust demand for a wide range of components, from chips to cooling systems, allowing suppliers to raise prices and boost margins. However, analysts warn this surge in profits may be short-lived, as the intense capital spending phase will eventually give way to lower-cost maintenance and upgrades once construction completes over the next few years.

Market behavior reflects this understanding. While share prices in leading AI firms have risen, gains have been modest relative to sharp profit increases. Valuation multiples, measured by price-to-forecast earnings ratios, have decreased, signaling that investors expect earnings growth to slow. For example, Nvidia’s valuation dropped from 23 times expected earnings to 15 times, even though its stock price increased approximately 15%. Similarly, Micron, a key memory-chip manufacturer, trades at a forward price-to-earnings ratio under five despite its shares tripling this year.

Some market participants view current earnings forecasts as overly optimistic, suggesting a potential earnings bubble. Gerard Minack of Minack Advisors highlighted that projected earnings for the top eight AI companies—Amazon, Alphabet, Broadcom, Meta, Microsoft, Nvidia, Oracle, and Palantir—plus a secondary group of AI-focused firms, have collectively increased by $700 billion this year. This contrasts with a $500 billion rise for the broader S&P 500 index.

The fragility of capital expenditure-related profits became evident recently as inflation surpassed expectations, pushing up borrowing costs and jeopardizing the AI construction surge. Data-center operator CoreWeave saw its stock plunge 24%, erasing all gains for the year. Memory-chip manufacturers Micron, Samsung Electronics, and SK Hynix also experienced significant declines, underscoring the sensitivity of AI supply chains to financial conditions.

The outlook remains uncertain. If investment in data centers and related infrastructure continues apace, the AI build-out could represent the largest U.S. capital spending initiative on record, potentially totaling $9 trillion by 2032, or about 3.2% of GDP annually, according to Columbia Business School professor Stijn Van Nieuwerburgh. However, for this expenditure to translate into lasting economic value, AI applications must boost productivity sufficiently to justify the costs, ensuring sustainable profits beyond the initial build phase.

Historical parallels offer mixed signals. Major capital investment waves in sectors like railways, electrification, and telecommunications eventually delivered widespread societal benefits but often disappointed investors in the short to medium term due to delays, lower-than-expected returns, and intense competition. AI faces similar risks, and investors must contend with the possibility that this time may not be fundamentally different from past technology booms.

This article was reported by synthesizing coverage from multiple independent news outlets to present a balanced, unbiased account. Read about our editorial standards. Spotted an error? Let us know.