Is the Tech Boom Ending? Why Experts Predict a Major Stock Market Drop by 2027

2026-09-16 economy

New York, Tuesday, 15 September 2026.
A major macroeconomic research firm, Capital Economics, warns that the artificial intelligence boom has entered its late stages, setting up the stock market for a severe correction. Analysts forecast that the S&P 500 could fall by up to 30% by 2027 as overstretched valuations, soaring corporate spending, and lagging profit returns reach a breaking point. With global AI investments projected to reach $1 trillion in 2026, technology capital expenditure as a share of U.S. gross domestic product has now surpassed levels seen at the peak of the dot-com bubble. Although strong underlying earnings may prevent a crash as deep as the 2000 tech bust, financial experts warn that current market expectations remain dangerously unsustainable.

Capital Economics Forecasts Market Correction

Capital Economics released a report on Monday, 14 September 2026, warning that the artificial intelligence market boom is entering its late stages [1][2]. The firm expects the S&P 500 to end 2027 at 6,500, compared with 8,250 at the end of 2026, implying a decline calculated as 21.212 percent from the projected 2026 peak [1][4]. John Higgins, chief economic adviser for financial markets at Capital Economics, stated there are plenty of signs that the market is now in the late stages of an AI bubble [1][4]. The firm suggests the eventual peak-to-trough decline could be at least 30%, a drop seen only seven times in the past century [4][5].

Valuation Risks and Capital Expenditure

Several indicators support the warning of overstretched valuations and excessive spending. U.S. technology capital expenditure has risen to a larger share of GDP than at the peak of the dot-com boom [1]. Global capital expenditures on AI-related projects are projected to reach $1 trillion in 2026, with $581 billion of that investment occurring in the U.S. [2]. Equity issuance has surged, and the market has become increasingly concentrated in a small number of companies [1]. Capital Economics points to these factors alongside lagging monetization as severe correction risks [1][3].

Earnings Expectations Versus Economic Reality

Despite the risks, the potential decline may be less severe than the roughly 50% fall during the dot-com bust because today’s AI boom has been driven more by earnings growth [1]. However, Capital Economics questions whether analysts’ expectations for earnings growth can remain this strong relative to U.S. economic growth [1][2]. James Reilly, senior markets economist at Capital Economics, noted that while AI will be transformative, profits may not reach analysts’ expectations [2][5]. A Bank of America survey found that 45% of investors identified an AI bubble as the biggest tail risk [1].

Broader Economic Implications and Debt Exposure

The economic footprint of AI is substantial, with ING Global Market Research reporting that AI-related investments account for one-third of U.S. economic growth in 2026 [8]. However, the financial structure involves significant risk; since 2013, over US$3.1 trillion has been invested in American AI, much financed by debt pinned to unproven revenues [6]. US AI hyperscalers and labs carry US$356 billion in long-term debt and US$248 billion in lease liabilities [6]. A potential collapse could extend beyond equity markets to credit markets and household portfolios [6]. Meanwhile, market volatility was evident on 14 September 2026, when several tech stocks tumbled [7].

Sources

Stock Market AI Bubble