Nasdaq Plunge Triggers AI Debt Crisis: Trillions in Capital Shift to US Treasuries

According to Woofun AI, in mid-October 2026, a fierce battle over long-term capital pricing power erupted in the global capital markets, with AI infrastructure companies and sovereign governments becoming the two core players in this game. The apparent pullback in tech stocks concealed deeper structural conflicts: the Nasdaq index fell about 4.5% within a week, while the Philadelphia Semiconductor Index lost over $1.6 trillion in market value.

This phenomenon is not a simple mood swing in the market—it’s a dramatic rebalancing as capital reevaluates the boundaries between risk and return, making sharp choices between the highly leveraged AI industry chain and risk-free sovereign assets. As bond yields of new-generation cloud service providers such as CoreWeave (CRWV.US) surged above 15%, with credit default swap costs implying a five-year default probability of over 60%, the yield on the 10-year US Treasury briefly spiked before retreating to around 5.1%, marking a significant rise in risk aversion in the market.

This shift in capital flows profoundly reveals the direct competition between aggressive expansion by the private sector and the financing needs of the public sector, fundamentally reshaping the underlying logic of global capital markets.

The degree of divergence in market performance far exceeds the modest overall index decline, with extreme asymmetry in the impact across sub-sectors. Although the Nasdaq 100 fell around 5% overall, the trend of funds moving from the highly leveraged AI industry chain to relatively safe assets became glaringly apparent at the individual stock level. Dell (DELL.US) saw its share price plunge nearly 20% in the short term; CoreWeave (CRWV.US), at the forefront of the AI compute arms race, dropped nearly 25% in a single week, with daily swings exceeding 15% on some trading days. In contrast, tech giants like Microsoft (MSFT.US), Apple (AAPL.US), and Oracle (ORCL.US) suffered smaller declines but were not immune to overall market pressures.

This divergence is not random market noise but a direct result of investors repricing the vulnerabilities of highly leveraged AI industry chains. Once the market recognized the risk of broken debt chains at some AI infrastructure companies, capital quickly fled high-risk targets in favor of safer havens, creating significant valuation compression and liquidity differentiation within the tech sector.

The core trigger of this market turmoil lies in the extreme fragility of the AI infrastructure companies’ debt chains. Take Nvidia (NVDA.US)-backed AI cloud provider CoreWeave (CRWV.US) as an example. By the end of June 2026, its total debt and lease obligations reached as high as $52 billion, with pure debt at around $35.6 billion. Even more concerning, its net interest expense in Q2 doubled year-on-year to $640 million. With rising financing costs, CoreWeave’s bonds due in 2031 briefly yielded near 16%, while their price fell below 80 cents on the dollar, officially entering distressed-debt territory.

Meanwhile, some of Oracle’s (ORCL.US) data center project loans have already started trading at a discount, and the debt sizes of hyperscalers like Amazon (AMZN.US) and Alphabet (GOOGL.US) continue to expand. Data compiled by Woofun AI suggests that if the current investment pace continues, AI-related infrastructure spending could reach several trillion dollars by 2030. However, the projected service revenue is far below this level, and some analysts even indicate there could be several trillion dollars in potential impairment risks. The market is now questioning a key assumption: Whether the massive capital outlays for AI infrastructure can generate enough cash flow in the foreseeable future to cover the increasingly heavy debt burden.

In this capital contest, the US government also faces immense refinancing pressure, forming direct competition with AI companies. Federal debt has surpassed $40 trillion, requiring vast amounts of maturing debt to be rolled over each year—making trillions held by pension funds, insurers, foreign central banks, and sovereign wealth funds the central prize. Money managed by BlackRock (BLK.US), Vanguard, and other large institutions frequently reaches trillions, and their allocation choices directly impact market pricing. AI companies have a clear and aggressive financing logic: they claim to possess transformative technology, requiring massive upfront capital to build data centers and procure GPUs to train next-generation models and eventually provide services to end-users. Their primary funding source is debt, with investors lending in exchange for interest rates ranging from 5% to 15%. The debt balances of hyperscalers such as Amazon (AMZN.US), Oracle (ORCL.US), and Alphabet (GOOGL.US) have risen sharply in the past three years; Oracle’s debt now approaches more than half its market value.

However, when investors start to worry about a potential bubble in the AI sector, slowing demand, or rising deflationary pressures, they prefer to lock in the currently high yields on Treasuries. The brief spike of 10-year Treasury yields to around 5.3% before pulling back is a reflection of this safe-haven demand—government bonds are seen as nearly risk-free because, in theory, the US, having the power to issue currency, cannot default.

The debt structure of the AI industry chain faces clear mismatches in maturity and yield, exacerbating market concerns. Data center leases often last 10–15 years, while customer contracts are much shorter. Companies borrow at high costs, but actual capital returns during the early stages can be well below the cost of financing. Some analyses indicate new cloud providers face borrowing costs near 9%, yet returns on capital might be as low as 1%, resulting in ongoing negative cash flow pressure. Even hyperscalers with strong balance sheets can’t fully escape this pressure. Their capital expenditure in 2026 has already approached or surpassed operating cash flow, and the proportion of debt financing has risen from below 10% to over 30%.

Global AI-related debt issuance dropped sharply to $23 billion in September 2026, well below the June peak of $113 billion, indicating a rapidly tightening financing environment. Banks have started to grow wary of concentration risks, with some project loans entering stress territory. The classic dilemma returns for investors: high returns come with high risks. The risk premium for lending to established tech giants is entirely different from fast-growing new cloud service providers. When the market becomes skeptical that end-user payment capacity will not be enough to cover the entire debt chain, risk appetite quickly reverses and capital shifts toward the certainty of government bonds. Even with inflation data remaining robust, 10-year Treasuries continued to rally due to safe-haven buying. Investors’ logic is simple: if an AI bubble bursts, demand slows, economic growth falters, and inflation cools, future rates may drop—so locking in over 5% yields now holds value.

This migration is not a wholesale sell-off of risk assets, but a reallocation of risk budgets, with some funds shifting out of Nasdaq-related positions and into Treasuries, creating a phase of “AI under pressure, Treasuries benefit.” The approaching midterm elections have also heightened uncertainty, and the market prefers lower risk exposure before clear policy guidance emerges. The essence of this adjustment is a reassessment by capital markets of the gap between “technological optimism and capital reality.” The long-term potential of AI technology itself has not been denied, but the pace of debt-driven expansion, the uncertainty of return cycles, and direct competition with sovereign financing needs are forcing investors to recalculate risk premiums. Real-world constraints in data center construction—such as power supply, regulatory delays, and equipment cost increases—further amplify worries, with some projects already delayed and higher financing costs set to squeeze future profit margins.

Meanwhile, hyperscalers are maintaining high levels of capital spending, underscoring the industry’s prioritization of competitive positioning over short-term cash flow pressure. From a broader perspective, the capital battle exposes a structural feature of the modern financial system: when technological change requires massive upfront investment, competition between the private and public sectors for long-term savings intensifies significantly. The status of Treasuries as the benchmark risk-free asset is thus reaffirmed, while highly leveraged growth assets must prove they can generate enough real returns. Whether the market can stabilize depends on three key variables: first, whether AI service revenues can be realized quickly enough to support debt repayment; second, whether financing costs will continue to rise or central bank policies will shift to easing; and third, how the relative attractiveness of sovereign versus corporate debt issuance evolves.

If further signs of economic slowdown appear, the safe-haven attributes of Treasuries will remain strong; if AI applications rapidly commercialize and generate substantial cash flow, the debt pressure on highly leveraged firms may ease. The market is currently in a “wait-and-reprice” phase, where any news of slowing demand or project delays could trigger further volatility. Capital is never unlimited—when AI companies and governments simultaneously reach for the same pool of funds, price mechanisms inevitably come into play. The outcome, as investors vote with their feet, is a compression of risk asset valuations and a phase of favoring safer asset yields. This is not simply the collapse of a technology bubble, but a profound rebalancing of capital scarcity. The market’s fate over the coming months will depend on whether this rebalancing occurs in an orderly fashion, rather than morphing into a broader credit crunch.