Oracle lost roughly $80 billion in market value on Dec. 11 when revenue missed expectations, and management hiked AI-related capex from $35 billion to about $50 billion, funded in part with rising debt.
The stock dropped up to 16%, dragging Nvidia, AMD, and the broader Nasdaq lower.
Reports framed the move as fanning “AI bubble” fears, with investors questioning whether the payoff from building massive data-center capacity is arriving fast enough to justify those costs.
On the same tape, Bitcoin slipped below $90,000, likely due to worries over the AI sector denting risk appetite.
The single-day episode encapsulates Bitcoin’s new structural vulnerability: it has become the high-beta tail of the AI trade, moving in lockstep with tech equity sentiment and bleeding harder when AI-linked stocks crack.
The correlation between Bitcoin and Nvidia reached approximately 0.96 over a rolling three-month window leading into Nvidia’s November earnings, according to analysis from 24/7 Wall St.
Regarding Nasdaq, The Block data shows that the 30-day aggregate Pearson Correlation coefficient was 0.53 as of Dec. 10.
Additionally, Bitcoin is down 22% since the Fed began easing interest rates on Sept. 17, while the Nasdaq is up 6%. This suggests that when tech stocks crash, Bitcoin tanks harder.
The AI bubble narrative has matured rapidly over the past few weeks.
Reuters reported in late November that AI-linked valuations and macro gauges such as the Buffett Indicator have pushed overall US equity valuations beyond dot-com-era extremes, while AI-heavy indices show sharp pullbacks and rising volatility even as enthusiasm remains high.
Besides, big tech companies have raised hundreds of billions of dollars in bonds this year to finance data centers and hardware. Morgan Stanley estimated a funding gap of around $1.5 trillion for the AI infrastructure build-out, and Moody’s chief economist Mark Zandi warned that AI-related borrowing now exceeds tech’s run-up before the dot-com crash.
Essays in The Bulletin of the Atomic Scientists and The Atlantic both cite roughly $400 billion in AI spending this year against only about $60 billion in revenue.
The math implies that most firms are deeply loss-making and that the wider economy is now partly leaning on an AI investment boom that cannot last indefinitely.
The liquidity mechanism that makes an AI bust worse for Bitcoin
If the AI bubble bursts, the damage to Bitcoin will go beyond simple correlation, as AI capex increasingly becomes a credit story.
Estimates indicated that AI-related data center and infrastructure financing deals jumped from about $15 billion in 2024 to roughly $125 billion in 2025, driven by bond issuance, private credit, and asset-backed securities.
Analysts in a Reuters piece compare some of the structures and opacity to pre-2008 patterns and warn of “untested risks” if tenants or cash flows disappoint.
Central banks now treat this as a financial-stability problem. The Bank of England’s recent stability update explicitly highlights stretched valuations in AI-focused firms. It also warns that a sharp correction in AI-linked equities could threaten broader markets via leveraged players and private-credit exposures.
The ECB’s November 2025 Financial Stability Review makes a similar point: the AI investment boom is increasingly funded through bond markets and private capital, making it more exposed to swings in risk sentiment and credit spreads.
Oracle is the poster child. Its $50 billion capex plan for AI data centers, alongside a roughly 45% jump in long-term debt and record credit-default-swap spreads, represents exactly the sort of over-extended balance sheet regulators worry about.
If an AI bubble pops, those spreads widen, refinancing costs jump, and leveraged funds that were long AI-themed debt and equities are forced to cut gross exposure. Bitcoin sits at the end of that chain.
Chinese researchers’ analysis of Bitcoin versus global liquidity finds a strong positive relationship between Bitcoin prices and global M2 or broad liquidity indices. Their paper called BTC a “liquidity barometer” that performs well when global liquidity is high and poorly when it contracts.
The liquidity story is straightforward: if the AI bubble bursts and forces a credit squeeze, the first-order effect is a global de-risking and liquidity pullback.
Bitcoin is one of the first things macro and growth funds sell when margin calls come in, and its outsized sensitivity to liquidity makes the drawdown worse.
Act two: how the policy response could fuel Bitcoin’s next bull cycle
The other half of the story is what happens after the first wave of deleveraging.
The same institutions that worry about an AI-driven correction also implicitly point toward the likely response. If over-levered AI and credit markets wobble hard enough to threaten growth, central banks will re-ease financial conditions.
The IMF’s latest Global Financial Stability Report warns that AI-driven equity concentration and stretched risk asset valuations make a “disorderly correction” more likely and stresses the need for careful, but ultimately supportive, monetary policy to avoid amplifying shocks.
History gives a template. After the COVID shock in March 2020, aggressive quantitative easing and liquidity provision coincided with a massive rise in total crypto market cap from around $150 billion in early 2020 to roughly $3 trillion by late 2021.
A recent Seeking Alpha report mapped Bitcoin against global liquidity and the dollar index shows that, once easing starts in earnest and the dollar weakens, BTC tends to put in large upside moves over the following quarters.
The narrative rotation also matters. If AI equities go through a classic post-bubble hangover, with lower multiples, negative headlines, and political backlash over wasted capex, some portion of speculative and macro capital could rotate into a different “future of money” or “anti-system” bet.
Bitcoin is the cleanest non-corporate candidate.
Recent market stress has already seen capital concentrate back into BTC rather than alts. As liquidity thinned and volatility rose recently, Bitcoin’s dominance has climbed to around 57%, with ETFs serving as the institutional on-ramp.
Additionally, although Bitcoin has recently shown a correlation with tech stocks, decentralization and scarcity remain the core of the “hedge” narrative.
The trade-off Bitcoin can’t escape
Bitcoin’s structural problem is that it cannot decouple from the AI trade in the short term, but it depends on policy responses to an AI bust for its medium-term upside.
In the immediate aftermath of an AI credit crunch, Bitcoin bleeds because it is the high-beta tail of macro risk, and global liquidity contracts faster than most assets can adjust.
In the months that follow, if central banks respond with renewed easing and the dollar weakens, Bitcoin historically has captured outsized gains as liquidity flows back into risk assets and speculative narratives reset.
The question for allocators is whether Bitcoin can survive the first hit well enough to benefit from the second wave.
The answer depends on how violent the AI correction is, how quickly policy pivots, and whether institutional flows through ETFs and other vehicles hold or break under stress.
Oracle’s Dec. 11 earnings miss is a preview: Bitcoin dropped below $90,000 in the same tape that wiped $80 billion off Oracle’s market cap, showing that the correlation is live and the sensitivity is real.
If the AI bubble fully unwinds, Bitcoin takes the punch first. Whether it emerges stronger depends on what central banks do next.
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