According to a report by International Business Times, in recent years, U.S. tech giants such as Microsoft, Google, and OpenAI have launched an intense race in the AI field, pouring massive investments into infrastructure for computing power and large model development, driving global AI investment fervor to its peak. However, the growing disconnect between enormous capital expenditures and actual returns has become increasingly evident, fueling ongoing debates on Wall Street about whether an “AI bubble” is about to burst. Recently, several international investment banks released reports highlighting underlying concerns behind the AI boom. A latest report from Goldman Sachs, projected for 2026, indicates signs of a bubble emerging behind the AI investment surge. The report states that from 2025 to 2027, leading U.S. tech companies are expected to spend up to $1.4 trillion on AI infrastructure, yet their average return on investment is significantly below market expectations, exposing much of this spending to risks of technological obsolescence and potential sunk costs. The report emphasizes that current AI investments exhibit a pattern of “heavy spending with light returns,” as some tech firms blindly ramp up computing infrastructure to secure market position while neglecting the feasibility of commercialization. OpenAI recently secured $110 billion in funding, pushing its pre-money valuation to $730 billion, though its profitability remains uncertain. Other international investment banks have also issued warnings about the risks of an AI bubble. Currently, the debate over an AI bubble continues on Wall Street. In the future, as technological iteration progresses, market perceptions become more rational, and commercialization accelerates, the AI sector may undergo a period of industry adjustment.
Information sourced from foreign official websites, China Trade Remedy Information Network, and other sites