Market economist Torsten Slok warns that the current AI-driven market bubble is more stretched than the dot-com bubble of the late 1990s, with top S&P 500 companies trading at a 12-month forward P/E ratio of around 25, surpassing the peak of the internet stock craze.

Citi analysts suggest that stocks might continue to rise due to an AI bubble forming, potentially peaking before AI-related capital expenditures reach their maximum.

Investors are overly optimistic about an AI future, often ignoring risks such as regulatory hurdles, high operational costs, and slower-than-expected adoption rates.

This narrow rally, heavily dependent on a small group of top companies, increases market vulnerability to fluctuations in their performance, raising concerns about a potential correction.

If corporate earnings do not meet these lofty valuations, the market could face a significant downturn, eroding investor confidence and causing substantial losses.

Historically, bubbles burst when expectations outpace reality, and current investor willingness to pay for future profits that may not materialize soon is a key concern.

While some strategists see signs of a bubble, the absence of a dovish Federal Reserve keeps the risk at about 25% by the end of 2026, according to UBS.

Market veteran Ed Yardeni warns of a 'melt-up' mode—rapid, unsustainable stock price increases—as the S&P 500 hits new highs in July 2025.

There are striking parallels between current AI investment trends and the late 1990s dot-com overvaluation, with many companies promising AI breakthroughs without solid revenue backing.

Investors' optimism about AI is inflating stock prices based on future promises rather than current earnings, fueling concerns about an impending bubble.

Discussions of an AI bubble have intensified on Wall Street since late 2022, following the surge in AI-related stock investments sparked by ChatGPT.

Industry leaders like Alibaba's Joe Tsai and tech executive Tom Siebel have echoed warnings about the potential AI bubble.