Arthur Hayes said in his latest essay, “Situationship,” that an eventual AI bubble burst could end up expanding global liquidity and act as a catalyst for Bitcoin’s next bull market, according to BlockBeats on Aug. 5.
Hayes argued that the key to deciding whether AI is in a bubble lies in how investors define AI infrastructure spending. He said markets broadly treat trillions of dollars in AI capital expenditure as technology investment and assign it high-growth valuations, while its underlying nature is closer to real estate investment.
He wrote that the current AI buildout is, in practice, the construction of base-layer assets that carry computing capacity, including data centers and power facilities, rather than direct investment in technology companies such as Apple.
“Financial institutions, private credit funds, and governments may mistakenly believe that investing in AI data centers is the same as investing in tech giants, when in reality it is more like investing in highly leveraged infrastructure projects,” Hayes said.
In his view, the core reason an AI bubble would break is not that companies fail to deliver profits, but that credit expands too far. He said that with support from the U.S. and Chinese governments, financial intermediaries could overbuild data centers, power facilities, and related supply chains, creating a credit-cycle risk more similar to the 2008 financial crisis than the earnings and valuation crisis seen in the 2000 internet bubble.
Hayes still said AI has substantial long-term value. He argued that the computing resources running inside data centers will drive the development of “silicon-based life” and have a far-reaching effect on human civilization comparable to the railway era.
On market impact, Hayes said that after an AI bubble burst, governments and central banks could adopt more aggressive monetary easing and use large-scale money creation to repair the financial system. That, he said, would push risk assets back into an upward cycle and ultimately benefit Bitcoin.
Hayes added that the central variable in the current AI cycle is whether capital markets have mispriced AI infrastructure, and that judgment will shape where markets go next.