국외연구자료 | KDI 경제교육·정보센터

KDI 경제교육·정보센터

Economic Information and Education Center

최신자료

Financial bubbles are notoriously hard to predict. From 1636-1637, when Dutch tulip prices went through the roof before collapsing spectacularly, to the buildup in stock prices in the late 1920s that eventually led to the Great Depression, or the dot-com meltdown of 2000, bubbles have often caught people by surprise. As recently as 2008-2009, the high prices of housing and financial assets unexpectedly collapsed and destroyed billions in valuations. Today, high stock prices driven by a relatively small number of tech companies emboldened by the AI boom have led some to ask whether we are on the precipice of an AI bubble. As noted recently in The New York Times, “80 percent of U.S. stock gains this year came from A.I. companies.” The dramatic market gains raise questions about whether the billions spent on data centers to feed the current AI boom will generate sufficient returns to justify those investments. On one level, it is impossible to answer this question because, as history demonstrates, experts can rarely forecast bubbles before they actually burst. But I argue that six indicators could help us monitor current AI risks and the possibilities for dashed optimism: AI investments, the timelines of data center construction, AI adoption levels, AI price levels, company competition, and public trust in technology. Watching these indicators will help people anticipate whether the AI bubble pops or grows.

Brookings 2025.11.11