Facts:
Gita Gopinath, former Chief Economist and current Deputy Managing Director of the International Monetary Fund (IMF), warned about the potential consequences of a correction in U.S. stock indexes, predicting that such an event could have serious repercussions for the global economy.
In a recently published article, Gopinath stated that the stock market’s recent growth — fueled by the emergence of innovative technologies like artificial intelligence (AI) — appears to be due for a pullback.
“There are good reasons to worry that the current rally is setting the stage for another painful market correction,” she emphasized, adding that such an event could lead to an international crash due to the interconnectedness of global markets and the exposure of major European economies to these investments.
Comparing the anticipated crash to the early 2000s dot-com bubble, Gopinath predicted that the U.S. domestic economy could lose $20 trillion (around 3.5%), while international investors could face losses totaling $15 trillion — roughly 20% of the rest of the world’s GDP.
“Today, a market crash is unlikely to result in a short and relatively harmless economic slowdown like the one that followed the dot-com bust. Structural vulnerabilities and the macroeconomic context are more dangerous. We must be prepared for more severe global consequences,” she concluded.
Why It Matters:
Gopinath is among the many voices expressing concern about AI’s dominance as a driver of growth — a phenomenon that may be masking a slowdown in the traditional U.S. economy.
JPMorgan estimates that companies with significant exposure to AI now account for 44% of the S&P 500’s total valuation, up from 22% in 2022. This surge has contributed to nearly $5 trillion in wealth gains for American households in recent years.
This means that a crash would affect not only Wall Street but also Main Street, as stock investing has become increasingly popular thanks to recent gains. An AI-driven market downturn would trigger an economic slowdown not just for investors, but also for industries within the AI supply chain, such as energy and semiconductors.
