OpenAI CEO Sam Altman has recently suggested that the artificial intelligence (AI) industry is currently experiencing a bubble fear, as quoted on CNBC. He explained that while AI represents one of the most significant technological shifts in decades, the excitement around it has led to overinflated expectations from investors.

Altman sees similarity between the current environment to the dot-com boom of the late 1990s, which was hit hard when many Internet companies failed to materialize the euphoria into profits.

Warnings From Industry Leaders

Altman’s remarks mirror concerns raised by other influential figures in business and finance. Alibaba co-founder Joe Tsai, Bridgewater Associates founder Ray Dalio, and Apollo Global Management’s chief economist Torsten Slok have all cautioned that AI valuations may be overheating.

Slok has even argued that the present AI surge could be more inflated than the Internet bubble, pointing out that today’s most valuable companies in the S&P 500 are more stretched in valuation than they were during the 1990s. Note that between March 2000 and October 2002, the Nasdaq lost nearly 80% of its value.

Analysts Divided on the Bubble Narrative

Not all analysts think that the entire AI market has entered bubble territory. Some experts argue that the fundamentals of AI and semiconductor supply chains remain strong and that the long-term growth prospects justify continued investment. However, many fear that capital is being invested in companies with weaker fundamentals, which may cause problems later on.

Rising Competition From Low-Cost Chinese Peers

The concerns intensified earlier this year when the “Magnificent Seven” had fallen from grace due to factors such as new, cheaper-cost AI entrants (e.g., DeepSeek) and individual companies’ ability to handle broader macro uncertainty.

DeepSeek, a Chinese startup developing AI models, revealed in late January that training the R1 model cost just $5.6 million, significantly less than the $100 million required to train OpenAI's GPT-4 model.

On the other hand, Alibaba (BABA Quick QuoteBABA - Free Report)  introduced the QwQ-32B model, an AI system that rivals DeepSeek but requires only a fraction of the data. Such advancements triggered doubts that the huge capital investments deployed by U.S. tech majors to develop AI technologies will generate the expected returns at all.

Rocky Journey of ChatGPT-Fame Open AI

Although the credibility of these claims has been questioned, the development has raised questions about whether current spending levels in AI are sustainable. Despite OpenAI’s huge success and its annual recurring revenue projection to top $20 billion this year, the company remains unprofitable.

The rollout of its latest GPT-5 model has also been anything but smooth, with some users finding it less intuitive than expected.

Nasdaq-100 ETF in Focus

Most AI biggies have exposure to the Nasdaq-100-based exchange-traded fund (ETF) Invesco QQQ Trust, Series 1 (QQQ Quick QuoteQQQ - Free Report) . The P/E ratio of QQQ stands at 59.27X. The 10-year range of the P/E ratio is 19.7X to 59.46X. The median P/E of the past 10 years is 25.8X. This shows the overvaluation concerns associated with QQQ.

However, the price-to-book (P/B) ratio of QQQ is currently 3.6X, which is the lowest value considering the past 10-year range. The 10-year median P/B is 6.03X, per Gurufocus.com. Moreover, with the Fed likely to cut rates in the coming months amid a weakening labor market, the growth stocks of QQQ should see some tailwinds.

Hence, the sudden crash of AI euphoria (if there is any) may not hurt QQQ that hard. Still, investors should be mindful of relentless AI investing going forward. Their portfolio may need diversification at the current juncture.

Note that the annualized return of QQQ is 18.78% over the past 10 years, while it is 21.23% over the past three years (due to the AI rally).