Arthur Hayes, chief investment officer of crypto investment firm Maelstrom, argues that a major cryptocurrency bull run could emerge despite current concerns about artificial intelligence and encryption. Hayes contends that AI-related anxieties represent another "wall of worry" that crypto has faced at previous market cycle beginnings.
Hayes compared today's AI concerns to three earlier periods of market stress: Bitcoin's 2017 block-size disputes over transaction capacity, pandemic-related disruption, and the aftermath of FTX's 2022 collapse amid rising interest rates. He characterized this year's anxiety as FUD, industry shorthand for fear, uncertainty, and doubt, in an October 8 post on X.
Money Printing as a Bullish Driver
Hayes bases his bull-market outlook on the expectation that government efforts to manage borrowing costs will support digital assets. In an August 24 essay, he argued that expanding dollar liquidity could flow into bitcoin and other cryptocurrencies, with financial conditions serving as a key driver of investment demand.
Hayes specifically cited U.S. Treasury bond repurchases as supportive of crypto prices. He distinguished these debt-management operations, which purchase outstanding government securities, from Federal Reserve asset purchases. In his framework, capital released through government intervention could reach speculative investments including cryptocurrencies.
Hayes also outlined an AI-bust scenario in which significant financial stress from heavily financed infrastructure could trigger multitrillion-dollar government support around 2027 or 2028, as data-center commitments come due. He suggested that resulting money creation could benefit crypto.
Cryptography Experts Push Back on Security Claims
The encryption concerns Hayes dismissed have drawn technical objections from specialists. Yehuda Lindell, head of cryptography at Coinbase, disputed claims of an imminent AI breakthrough capable of breaking established cryptographic assumptions, stating there was no evidence for such a development.
AI-assisted security research has demonstrated both vulnerabilities and strengths in existing crypto systems. A researcher using AI tools identified a flaw in Zcash's shielded transaction system, illustrating how automated analysis can uncover software weaknesses in older code. Developers patched the vulnerability within days of discovery, though the issue involved a software defect rather than a break in the mathematical protections underlying digital signatures.
