AI三大“巨雷”，美股噩梦

Core Viewpoint - Despite the solid foundation of AI investment themes, Barclays highlights that a slowdown in data center capital expenditure could pose the largest systemic risk to the U.S. stock market, with a potential 20% decline in capital spending leading to a 3-4% downward pressure on S&P 500 earnings and a 10-13% drop in valuations [1][30]. Group 1: Potential Risks - The report identifies three major potential "landmines" that could trigger this crisis: 1. Technology and Efficiency Risk: Rapid improvements in AI model efficiency may lead to overbuilt computing facilities, reminiscent of the "dark fiber" tragedy during the dot-com bubble [2][9]. 2. Physical Limitations Risk: Increasing electricity shortages are becoming a hard constraint on data center construction, potentially cooling capital expenditures [2][14]. 3. Liquidity Risk: As capital expenditure growth begins to exceed cash flow generation, financing pressures and dwindling VC capital could become critical issues [3][20]. Group 2: AI Investment Fundamentals - The report affirms the robust foundation of AI investment themes, noting that even with an expected annual growth of 30% in capital expenditures, the demand for computing power still far exceeds supply [4][5]. - The capital expenditure to sales ratio for current tech giants is approximately 25%, which is considered relatively prudent compared to over 40% during the telecom bubble [6]. Group 3: Economic Impact - Barclays emphasizes that a slowdown in data center investment could significantly impact the overall U.S. economy, contributing about 1 percentage point to the 1.4% GDP growth forecast for the first half of 2025 [25][28]. - The negative resonance between macroeconomic factors and industry-specific issues poses a greater threat to the stock market than isolated industry adjustments [29]. Group 4: Earnings and Valuation Impact - The analysis indicates that a 20% decline in data center capital expenditure over the next two years would have a relatively mild impact on earnings per share (EPS), with a projected 3-4% drag on S&P 500 EPS for fiscal year 2026 [31]. - However, the impact on valuations would be severe, potentially leading to a 10-13% compression in the overall S&P 500 index, with sectors directly benefiting from AI infrastructure facing average P/E compression of 15-20% [32][33].