The global artificial intelligence market is in a moment that few dare to openly question.
While the enthusiasm around AI stocks keeps pushing valuations to historic levels, two of the most respected hedge fund managers in China have decided to raise a red flag right in the middle of the party. 🚩
Wealspring Asset, founded by Yang Dong, and Shanghai Banxia Investment Management Center are saying, loud and clear, that the AI boom in global markets may have gone way too far.
The term they used is anything but gentle: super bubble.
And when fund managers with that kind of track record use that word, it is worth stopping and listening to what they have to say.
But what exactly is a super bubble in the context of artificial intelligence? And why should signals coming from Chinese funds matter to anyone following the tech sector around the world?
That is exactly what we are going to break down here. 👇
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What the Chinese Fund Managers Actually Said
Before diving into the explanations, it is worth understanding exactly what was said. According to a letter sent to investors and seen by Bloomberg News, Wealspring Asset stated that global AI stocks have turned into a super bubble and that the point of collapse may not be that far off. Yang Dong, the founder of the firm, gained notoriety in China precisely for calling the market top in 2007, which gives his words some serious weight.
Shanghai Banxia Investment Management Center was even more direct, declaring that the trigger for the AI bubble burst has already appeared. The firm specifically cited the pressure on the accelerated revenue growth at Anthropic, one of the most talked-about companies in the large language model space, as a sign that expectations may have drifted too far from reality.
These are two warnings coming from different sources, but they point in the same direction: the global market enthusiasm around artificial intelligence may have crossed the line of what makes economic sense.
What a Super Bubble Is and Why the Term Is So Alarming
A regular financial bubble is already concerning enough on its own. It happens when the price of an asset rises far beyond what the actual economic fundamentals can justify. But a super bubble goes further than that. It is characterized by a cycle of optimism so intense and so widespread that it infects multiple sectors at the same time, creating a chain of dependency where one falling domino drags the others down in a cascade. In the context of artificial intelligence, we are talking about chip companies, cloud platforms, language model startups, infrastructure providers, and even retailers that somehow latched onto the AI narrative to boost their valuations.
What makes this scenario particularly delicate is that real growth does exist. AI is not a fraud, and the technological advances of recent years are concrete and measurable. The problem is not the technology itself, but the speed at which the global market started pricing the future of that technology into the present. When investors start paying today for what they think a company will be worth ten or fifteen years from now, the risk of distortion becomes enormous. Any negative signal, any result that falls below expectations, can act as a trigger for a swift and violent correction.
The managers at Wealspring Asset and Shanghai Banxia are pointing at exactly this disconnect. In their view, the current pace of valuation growth for AI-related companies does not reflect the real economic growth these technologies are generating right now. What is happening, according to this reading, is a collective projection of a very promising future being priced in at an accelerated and, in many cases, irrational pace — a classic euphoria-driven market move.
Why Chinese Hedge Funds Are Saying This Now
China has a pretty unique relationship with the tech sector and market cycles. In recent years, the country went through its own series of bubbles and corrections in sectors like real estate, education, and domestic technology. This created, in some local hedge fund managers, a sharpened sensitivity for spotting euphoria patterns before they turn into bigger problems. Yang Dong, at the helm of Wealspring, is known for navigating turbulent periods in the Chinese market precisely because he adopted a cautious stance when the dominant narrative was endless growth.
Beyond that, there is an important geopolitical angle to this analysis. The restrictions imposed by the United States on the export of advanced chips to China place Chinese fund managers in the position of outside observers watching the Western AI boom unfold. They see the movement from the outside, without the same level of emotional and financial exposure that many American or European investors carry. That distance can, paradoxically, offer a clearer perspective on where enthusiasm ends and where risk begins. It is like watching a party from outside the window — you notice things that the people inside can no longer see. 🎉
Another relevant point is the timing of these statements. Both funds chose to speak up at a moment when tech-heavy indexes were still at elevated levels and the overall sentiment across the global market remained optimistic. Talking about a bubble when everything is still going up takes conviction, and that is precisely why this kind of warning carries weight. Managers who only sound the alarm after a crash are not doing analysis — they are doing hindsight. Those who speak up beforehand take on real reputational risk, and that says a lot about the level of concern behind these statements.
The Anthropic Case and the Burst Trigger
One detail that deserves special attention is the direct mention of Anthropic by Shanghai Banxia. The company, creator of the Claude assistant, is one of the main references in the large language model space and has attracted heavy investment in recent years. When a fund manager points to the pressure on that company’s revenue growth as the trigger for a potential bubble, they are signaling something important: even the most promising companies in the sector face the challenge of turning cutting-edge technology into sustainable financial results.
This point is central. Building increasingly powerful AI models costs a lot of money, and training and infrastructure expenses grow fast. The question Banxia seems to be raising is whether the revenue generated by these companies can keep up with the pace of spending and, more importantly, the pace of expectations the market has already baked into stock prices. When that math does not add up, enthusiasm starts giving way to doubt. 🤔
What the Numbers Say About the Real Economic Growth of AI
To understand whether the warning makes sense, it is worth looking at what the data actually shows. The economic growth driven directly by artificial intelligence is still in a relatively early stage when compared to the size of the bets the market is making. Companies like Nvidia saw their stock prices multiply in a matter of months, supported by real demand for GPUs but also by expectations that this demand would keep growing at an exponential rate for years to come. The problem is that expectations do not pay bills, and the AI infrastructure investment cycle is already showing signs that the return on that capital will take longer than many anticipated.
Analyses from major global investment banks have already raised questions about when and how companies will turn the billions invested in AI into real, sustainable revenue and profit. The question is not whether AI will generate value — it will. The question is whether it will generate value on the timeline and at the scale the market has already priced in. And the honest answer, for now, is that nobody knows for sure. That level of uncertainty, combined with sky-high valuations, is exactly the kind of environment where bubbles form and eventually unravel.
The hedge funds raising this discussion are not necessarily betting against the technology. They are, in fact, separating two things the market insists on blending together: the real value of artificial intelligence as a transformative tool and the speculative value currently being assigned to it on stock exchanges around the world. This distinction is fundamental. It is entirely possible to genuinely believe in the potential of AI and, at the same time, recognize that the current price of many stocks in the sector already reflects a future that is far more certain and far faster than reality can guarantee.
What This Means for Anyone Following the Tech Sector
For those keeping an eye on the tech sector — whether as an enthusiast, a professional, or someone who simply wants to understand where the world is heading — the message from these fund managers is an invitation to think more carefully before taking the dominant optimism as absolute truth. The global market has a well-documented history of creating powerful narratives that function as reality for a while, until they stop working. The dot-com bubble in the early 2000s is the most cited example, but history is full of similar cycles in other sectors.
This does not mean that artificial intelligence is going to repeat exactly the same path as the dot-coms. The context is different, companies today have real revenues, and the technology itself is more mature and more broadly applicable than simple internet access was in the 90s. But it does mean that the pace of growth the market expects may not materialize on the expected timeline, and that a correction — even if not catastrophic — could profoundly reshape which companies and which bets survive the cycle.
The warning from the Chinese hedge funds, therefore, is not a signal that AI is going to fail. It is a reminder that markets operate in cycles, that euphoria and rationality rarely coexist for long, and that the most interesting voices during a bull run tend to be the ones asking uncomfortable questions when everyone else would rather celebrate. 🧠
Keep an eye on the next moves in the AI market. The conversations happening right now behind the scenes at major investment funds tend to hit the headlines a little later, and understanding the landscape before that happens makes all the difference.
