Jason Thomas of Carlyle Group believes an AI development slowdown is "more likely than not," injecting a note of caution into the market's enthusiasm for AI. This perspective diverges from that of AllianceBernstein Holding LP, whose fixed-income specialists, including senior investment strategist Thierry Taglione, contend that major technology companies will proceed with fundraising and capital spending plans irrespective of calls to moderate AI development. They characterize these as long-term fundraising strategies by hyperscalers and data-center operators.
The broader market context shows investors expressing nervousness regarding the AI-driven stock rally following warnings from industry leaders about the need to temper AI spending. Semiconductor stocks, for instance, experienced a downturn on Monday. The vulnerability of AI-related investments is also compounded by rising bond yields, which are simultaneously pressuring overall stock prices. This sentiment reflects growing anxiety among tech investors about the potential for an AI slowdown.
Industrial and energy companies heavily invested in the AI buildout are particularly exposed to a potential slowdown. For example, shares of GE Vernova dropped almost 9%, Caterpillar sank over 4%, Vertiv fell close to 8%, and Oracle slipped almost 4% on Monday. This sell-off was partly triggered by a proposal from Anthropic CEO Dario Amodei over the weekend, suggesting a slower pace for frontier model development. While Amodei clarified that this doesn't mean halting model training, the market reacted with concern, indicating the sensitivity of these companies to any perceived deceleration in AI progress. Oracle's cloud infrastructure business, a key growth driver, is expected to face headwinds from a slowdown in model development and training, according to RBC Capital Markets equity analyst Rishi Jaluria.
Despite these concerns, some analysts, like Jennifer Lee of BMO Capital Markets, view an AI slowdown as potentially temporary. She argues that the fundamental infrastructure, investment, and demand for AI are unlikely to reverse course. However, she acknowledges that issues such as job displacement, data center pressures, and profitability concerns could moderate the pace of growth. Concurrently, the ongoing demand for AI-related debt is notable, with hyperscalers like Amazon raising approximately $6 billion and Alphabet raising about $10 billion through bond sales, although new debt deals in the fall are anticipated to be priced at significantly higher rates.
