OpenAI secretly submitted an IPO application, forming a $3.6 trillion listing queue with SpaceX and Anthropic, accounting for 10% of the total market value of the Nasdaq. The concentrated entry of these three giants will intensify the concentration risk in the U.S. stock market and extend the "circular capital structure" of mutual investments from private equity to the public market. Analysts warn that while the capital moat for AI has become a barrier, the technology is still in the early stages of engineering implementation, and the market should be wary of valuation bubbles and volatility risks.

Written by: Zhang Yaqi

Source: Wall Street Journal

OpenAI has secretly submitted an IPO application, joining SpaceX and Anthropic to form a queue of AI companies with a total valuation approaching $3.6 trillion, approximately 10% of the total market value of the Nasdaq, putting additional pressure on this already highly concentrated tech index.

OpenAI announced on Monday that it has secretly submitted an IPO application to the U.S. Securities and Exchange Commission (SEC). Anthropic announced last week that it completed a secret IPO application and raised $96.5 billion in a new round of funding, surpassing OpenAI for the first time; SpaceX plans to go public this week with an estimated valuation of about $1.8 trillion, which will place it among the highest-valued publicly traded companies in the world.

The combined valuation of the three companies is approximately $3.6 trillion, accounting for about 10% of the Nasdaq's total market value. Currently, the top ten constituents of the Nasdaq account for over 40% of market value weight, and if these AI giants all go public, it will further exacerbate index concentration, amplifying volatility risks in the technology sector. Meanwhile, the complex capital relationship between leading AI companies is extending from the private market to the public market, raising concerns among some market participants about whether current valuations contain bubble components.

This wave of AI IPOs will profoundly impact the asset allocation of passive funds and reshape global investors' exposure to risks in the technology sector. Behind the massive influx of capital, the commercialization process of AI technology remains in its early stages, and the long-term profitability and value creation paths of related companies still carry significant uncertainty.

Three AI Giants’ Valuation Approaches $3.6 Trillion

OpenAI announced on Monday that it has secretly submitted an IPO application, becoming the third major AI company to officially start preparing for an IPO after SpaceX and Anthropic. In terms of valuation, SpaceX is approximately $1.8 trillion, Anthropic is about $965 billion, and OpenAI is around $852 billion, totaling about $3.6 trillion. OpenAI's valuation comes from financing completed in March of this year, when the company raised $122 billion at an $852 billion valuation, surpassing SpaceX's overall IPO valuation in a single round.

According to Bloomberg, OpenAI is working with Goldman Sachs and Morgan Stanley to prepare for the IPO, with a potential listing window as early as this fall. The company stated that the exact timing of the IPO has not been finalized: "It may take a while because some things are easier to push forward as a private company. But this is a complex balance, and this move provides us the option to go public faster at the best timing." Reports indicate that OpenAI also plans to initiate a share buyback offer to employees for liquidity purposes a few weeks before the official listing, and the company spokesperson declined to comment on this.

Nasdaq Concentration Risk Intensifies, Market Warns of Circular Capital Structure

Songyee Yoon, founder and managing partner of Principal Venture Partners, pointed out in an interview with Bloomberg on the 10th that the $3.6 trillion AI IPO pipeline accounts for about 10% of the total market value of the Nasdaq, while the top ten constituents of the Nasdaq currently account for over 40% of market value weight. She stated that adding these AI companies will significantly increase Nasdaq concentration, "further exposing it to cyclical risks and volatility in the tech market."

Yoon also noted that the scale of passive funds continues to expand, and these AI giants have deep capital ties with each other. The intricate dependency relationships and mutual investment arrangements between leading AI companies are gradually extending from private equity into the public market, forming a "circular trading" pattern. "This is also one of the reasons people believe there may be some bubble component in the current AI market."

This concern is not limited to the U.S. market. Yoon pointed out that the dominant effect of U.S. tech giants on the global supply chain has led semiconductor and infrastructure companies worldwide to also be driven by capital enthusiasm, thereby supporting valuation exuberance in other markets.

Yoon believes that the dense IPO schedule of AI giants is backed by deep commercial logic: the capacity for large-scale financing itself has become a core component of their services and business models, forming structural barriers to new entrants. "The capital moat built around these companies has become part of their business characteristics—this is also one of the barriers against new entrants and one of the reasons behind this IPO boom."

AI companies are currently competing to raise hundreds of billions of dollars for purchasing chips, building data centers, and developing more advanced AI systems. Reports indicate that OpenAI informed investors in February that it plans to invest approximately $600 billion in AI infrastructure by 2030.

Technology Still in Its Early Stages, AI Application Layer Contains Greater Investment Opportunities

Yoon stated that AI is a real existing technology that has shown great potential in the "technology demonstration stage", but there is still a lot of work to be done before engineering implementation, cost optimization, and large-scale deployment. "From both the technological and infrastructural perspectives, we are far from the final stage and there is plenty of room for improvement." She also noted that these improvements may come from existing AI giants as well as from emerging companies focused on solving specific problems.

Yoon used the aviation industry as a comparison to explain the distribution logic of AI investment opportunities: there are very few companies that can build engines, but the aircraft manufacturing, airline operations, and supporting service industries derived from the aviation ecosystem are where the main economic value is created. "We have already found an extraordinary 'engine technology' with the potential to spawn entirely new business models. However, a lot of businesses and applications built upon it still need to be constructed, and it remains unknown where the ultimate value will be created, captured, and settled."