OpenAI CEO Sam Altman has publicly acknowledged that the current surge in artificial intelligence investments resembles a bubble similar to the dot-com crash of the early 2000s. Altman warned that investors are generally overexcited about AI, which could lead to market corrections, even as he and OpenAI plan to invest trillions of dollars in AI infrastructure in the near future. Supporting this cautionary stance, a recent MIT study found that 95% of corporate generative AI pilot projects fail to produce measurable returns, despite enterprise investments ranging from $30 billion to $40 billion. The study, based on extensive interviews and surveys, highlights that only about 5% of AI initiatives achieve rapid revenue acceleration, with the majority stalling and showing little impact on profit and loss statements. This data has contributed to growing concerns among investors and analysts about a potential AI-driven bubble in the tech sector. Bank of America strategist Michael Hartnett has also pointed out that the S&P 500’s price-to-book ratio has reached 5.3, surpassing the peak level seen during the 2000 dot-com bubble, further signaling possible overvaluation in the market. Despite these warnings, AI is still regarded as a transformative technology with long-term potential, though experts emphasize the need for patience and realistic expectations about short-term returns.