Then came the sharpest reversal on record. On July 31, the KOSPI soared 18% in a single session after the South Korean government announced a 20 trillion won ($13.9 billion) sovereign wealth fund injection for strategic AI investments, data centers, and infrastructure . The New York Times noted that prior to this upswing, the market had been in a downturn driven by fears that the $1 trillion+ in global AI investment "had been excessive"
.
The mixed signals continued into August. On August 1, South Korea reported that July exports beat forecasts, with semiconductor exports jumping 179% year-on-year on global AI chip demand . Yet this strong data sat uneasily alongside the preceding equity rout — reflecting a market that cannot decide whether current AI demand justifies the scale of capital being committed.
While equities grabbed headlines, credit markets were sending an even more alarming signal. Credit default swap (CDS) spreads for Alphabet, Amazon, Meta, and Nvidia hit record highs in late July, as investors grew more concerned about the debt being taken on to fund data centers, chips, and advanced models . CDS prices act as insurance against default; higher spreads signal growing concern about a company's ability to manage its debt.
The credit market, rather than equity valuations, became the leading indicator of stress — with CDS "overtaking EPS" as the key metric . Oracle's 5-year CDS was quoted at 215 basis points by late July, meaning investors needed to pay $215,000 annually to insure $10 million of debt against default
. Big Tech's credit insurance costs had more than doubled since early 2025
.
CNBC reported on July 24 and 26 that credit spreads for tech companies driving the AI buildout were widening sharply, with fixed-income investors increasingly uncomfortable with the sheer volume of capital needed . The numbers are staggering: hyperscaler bond issuance hit $182 billion in the first half of 2026 — a 1,300% year-on-year jump
.
Analysts flagged a troubling "circular financing" dynamic . The pattern works like this: Big Tech companies borrow heavily to buy Nvidia chips and build data centers, which in turn power AI services. But the ultimate end-user demand for those AI services remains unproven. If confidence in those returns pulls back, the whole loop could unravel — from Nvidia across the entire hyperscale cloud sector
.
The concern is that AI spending has moved from a speculative equity bet to a systemic credit exposure. Fitch itself named four possible triggers for a correction: AI commercial returns falling short, tighter regulation, intensifying competition, and labor-market disruption .
Fitch's outlook placed AI-correction risk on par with the U.S.-Iran military escalation and potential Hormuz blockade as the two biggest near-term threats to global credit . A third risk — a strong El Niño — was cited as adding pressure on junk-rated sovereigns
.
The warnings were not isolated. The Bank for International Settlements, in its June 2026 annual report, flagged the sustainability of AI-related investments as a key pressure point in global financial conditions . Man Group's H2 2026 Credit Outlook (July 9) noted that credit markets were "already feeling the weight" of hyperscaler bond supply, with rising issuance and falling interest coverage ratios likely to drive further spread widening
. Allianz Research (July 8) observed that while AI was propping up global growth and offsetting energy and trade war drags, rising AI-related bond issuance and deteriorating interest coverage ratios would likely drive a "mild widening in spreads" and a 4% increase in global insolvencies in 2026
.
The core concern — summed up in Fitch's phrase that AI spending is "running ahead of uncertain future returns" — has moved from an equity-market debate to a credit-market reality. In the span of a few days in late July 2026, investors saw South Korea's benchmark index swing by more than a third, CDS spreads for the world's biggest tech companies hit record highs, and a global bond market begin to reprice AI debt risk in earnest.
The trillion-dollar question — whether AI infrastructure spending will generate returns that justify its cost — remains unanswered. What changed in July 2026 is that the market started demanding an answer.