Arthur Hayes Predicts AI Debt Crisis Could Push Bitcoin to $1M by 2030

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Arthur Hayes, CIO of Maelstrom, has again predicted Bitcoin could hit $1 million by 2030, citing risks from debt-backed AI infrastructure spending. He warns that a slowdown in AI funding by 2027 or 2028 could trigger credit stress, prompting central banks to boost liquidity. This scenario could favor scarce assets like Bitcoin. With the bitcoin ETF approval on the horizon, demand for spot bitcoin ETFs may rise, further supporting Bitcoin’s long-term price trajectory.

Arthur Hayes has doubled down on one of the crypto market’s most aggressive long-term forecasts. He still argues that Bitcoin could reach $1 million by 2030 as a debt-fueled artificial intelligence boom potentially runs into trouble.

The Maelstrom chief investment officer reportedly sees late 2027 or early 2028 as a potential turning point, when slowing AI infrastructure spending could expose weaknesses in the enormous amounts of credit being used to finance data centers, chips and computing infrastructure.

Why an AI crash could become bullish for Bitcoin

Hayes’s argument is less about AI companies suddenly becoming unprofitable and more about what happens to the debt accumulated during the infrastructure boom.

In an earlier essay, he compared the setup with the 2008 financial crisis rather than the dot-com collapse, and argued that the biggest vulnerability could sit with lenders and infrastructure projects rather than the largest technology companies.

Essay by Arthur Hayes

The theory is straightforward: if AI-related projects struggle to generate enough cash to service their debts, losses could spread to banks, private-credit funds and other lenders. Governments and central banks could then respond by injecting liquidity into the financial system.

Hayes believes that monetary expansion would ultimately benefit scarce assets like Bitcoin and help propel BTC toward his $1 million target.

There are already signs that the financing side of the AI boom is attracting more scrutiny. Reuters reported on Sept. 30 that AI-related borrowing in the US leveraged-finance market has reached roughly $88 billion in 2026, compared with about $20 billion in early 2025. Investors have also become more selective about lending to riskier AI businesses.

The IMF pointed out similar concerns earlier this year. Citing Morgan Stanley estimates, it said data-center capital expenditure through 2028 could reach $2.9 trillion. This is way more than the cash flow available from hyperscalers, increasing the need for private credit, corporate debt and securitization.

Why 2027 could become a critical year

Hayes expects growth in announced AI capital expenditure to begin slowing during the second half of 2027, which could potentially reveal which projects were built on overly optimistic demand assumptions.

That makes his Bitcoin forecast highly dependent on a chain of events rather than simply continued crypto adoption. AI spending slows, credit losses emerge, policymakers respond with greater liquidity, and Bitcoin benefits from the resulting monetary expansion.

For now, Bitcoin is already showing signs of strength. BTC was trading around $83,895 on Oct. 1 after gaining roughly 0.6% over the past 24 hours.

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