Bitcoin Rally Stalls as AI Spending Drains Dollar Liquidity
Arthur Hayes says the reason Bitcoin (BTC) hasn’t surged despite broader money supply growth is that the AI spending frenzy is absorbing newly created dollar liquidity. In a new blog post, the BitMEX co-founder argues his earlier fiat-liquidity model missed “where that liquidity was actually flowing.”
Hayes points to the post–ChatGPT launch period (Nov 2022) as the start of what he calls the “great AI bubble.” He notes AI-linked equities have outperformed crypto: Nvidia gained roughly 11x versus BTC’s about 7x rise over a comparable window. The divergence reportedly accelerated from late 2024 as BTC later rolled over.
Central to the thesis is capital intensity. Hayes describes AI as needing massive financing for data centers, electricity, specialized chips, and supporting infrastructure. He cites public-disclosure estimates that AI firms issued about $1.5T in debt from Nov 2022 onward, with around $1.3T raised since 2025 as infrastructure spending surged. Comparing that with US M2 growth (also estimated near $1.5T), Hayes concludes AI effectively absorbed nearly all newly created dollar liquidity—“AI sucked up all created dollars.”
Separately, analyst “Doctor Profit” frames BTC’s move as part of a six-stage bear market cycle, warning of more volatility rather than a final bottom. He flags a potential cycle-low zone of $40,000–$48,000, possibly between Sep–Oct 2026.
Bearish
The article’s thesis is bearish for near-term BTC trading because it links Bitcoin’s relative underperformance to a structural flow problem: AI infrastructure investment is allegedly absorbing most newly created dollar liquidity. If liquidity is “rotating” to the tech/AI capital budget instead of crypto, BTC catalysts tied to money supply growth may fail to translate into price upside, which can pressure risk sentiment.
It also cites a bear-market-cycle framework (Doctor Profit’s five of six stages) and points to a lower prospective BTC range ($40k–$48k). Traders often react to such narratives by de-risking into support levels, increasing the probability of volatility around key bands.
Historically, similar liquidity-rotation moments (when capital concentrates into a high-capex tech sector) have tended to weaken speculative bid in other high-beta assets until the capital flow reverses. Long-term, if the AI capex cycle eventually matures and financial conditions loosen, the “liquidity finds crypto” assumption could reassert—but the timing risk is the key reason the impact is assessed as bearish for the short to medium term.