Big Tech Debt Hits $1.65 Trillion as AI Infrastructure Spending Triggers Credit Concerns

Big Tech credit risks rise sharply as AI spending soars

A closely watched gauge of risk in holding the debt of companies at the centre of the AI boom is rising rapidly, underscoring growing jitters over Big Tech's vast spending on data centres, chips and computer memory. Prices for credit default swaps, popular tools to bet against corporate debt, tied to Oracle, SpaceX, Alphabet, Amazon, Meta, Broadcom and Nvidia have risen to record highs in recent days, according to LSEG data. The sharp moves echo a sell-off in debt issued by so-called hyperscalers, which are piling hundreds of billions of dollars into developing vast data centres and sophisticated AI models. It comes as investors have grown increasingly worried about the deluge of debt sold by these companies. "Credit markets don't deal well with uncertainty, and the sheer unpredictability of the pace and cost of AI financing is triggering a serious crisis of confidence right now," said John Aylward, chief investment officer of credit manager Sona Asset Management. In a sign of waning investor interest in AI debt, Meta's latest borrowing cost for its $12bn Texas data centre has risen significantly to levels closer to junk-rated bonds. The debt "priced in line with where B- deals are currently trading . . . a quite remarkable situation, but that is the world we are living in today", Aylward said. The moves have been most acute at Oracle, whose five-year CDS was quoted at 215 basis points on Monday, up from 144 bps at the start of the year, meaning that investors now need to pay $215,000 annually to insure $10mn of debt against default. The database group last month said it would invest $70bn in the coming year to finance its data centre build-out, prompting S&P Global Ratings to downgrade its credit rating to triple B minus, just one notch above junk status, citing an uncertain path to profitability amid massive AI investments. "The big question is, will this level of [capital spending] grow in perpetuity and when is that inflection point where we will see positive cash flow again?" said David Brown, global co-head of investment grade at Neuberger Berman. "We won't have the answer anytime soon, which explains the weakness in performance." "It's potentially going to be a problem because there's still so much financing waiting to be done," Brown said. The concern is spreading beyond Oracle, with the cost of protecting Nvidia's five-year debt also hitting a record of 79 bps. The chipmaker is in talks to provide a $250bn guarantee to help OpenAI finance a massive data centre project, according to a person familiar with the matter. Nvidia declined to comment on the plan, which was first reported by The Wall Street Journal. Alphabet's CDS -- which only started trading in late November last year -- was also quoted at a new high of 67 bps on Monday, after the company's free cash flow turned negative in the second quarter for the first time since going public more than two decades ago. While investors assess the likelihood of default for investment-grade issuers as low, buying CDS had become a way for investors to protect themselves from future credit downgrades and market volatility, said George Catrambone, head of fixed income for the Americas at DWS Group. "Hedging is becoming more and more appropriate, especially after seeing these capex numbers post-earnings," Catrambone said. "A huge amount of debt was issued without necessarily being able to illustrate revenues yet. There's more and more scrutiny being placed." CDS has also become a broader market proxy for bearish bets on tech names. "For hyperscalers, watch CDS, not EPS," said Manish Kabra, head of US equity strategy at Société Générale, referring to earnings per share, a popular metric of stock valuation. "AI capex is still outrunning cash generation, driving [tech group's] free cash flow towards cycle lows," Kabra said. Additional reporting by George Hammond and Michael Acton

Massive AI ambitions push Big Tech deeper into hidden debt

Wall Street watches nervously as hidden AI debts fuel fresh fears * Hidden AI debts are attracting fresh scrutiny across America's biggest technology companies * Massive data centre spending is testing investor confidence like never before * Meta reportedly carries the largest off-balance-sheet obligations among the five companies An investigation by Nikkei Asia has claimed five of America's largest tech companies are reportedly concealing huge debts outside their official financial statements. Alphabet, Microsoft, Amazon, Meta, and Oracle together account for roughly $1.65 trillion in liabilities missing from their public balance sheets. That figure exceeds the $1.35 trillion these firms officially disclosed last quarter, with Meta alone holding roughly $420 billion off-balance-sheet. Echoes of Enron Analysts have begun drawing direct parallels to Enron, the energy trading company whose 2001 collapse remains a cautionary tale in corporate finance. Like Enron once did, these tech giants rely on special purpose vehicles, essentially legally separate subsidiaries, to keep debt off their books. Such arrangements can make a company's financial reporting appear far healthier than the underlying reality actually supports at any given moment. This accounting structure remains legal when applied correctly, although critics argue it can complicate efforts by investors to measure overall financial exposure accurately. "The accounting treatment itself is in fashion," technical accounting consultant Tom Selling told Bloomberg. "But what if one of these companies was a house of cards and was propping itself up with this accounting treatment? To me, that's the risk." The warning has encouraged renewed scrutiny of corporate reporting practices across the technology sector, particularly among the companies named in the investigation. This scrutiny comes as firms continue spending heavily to expand the computing capacity required for increasingly sophisticated artificial intelligence systems. Mounting financial pressure To remain competitive in the AI race, these companies are committing enormous sums toward massive, long-term data center construction projects. The scale of planned data center spending across the entire industry has reached levels rarely seen in corporate history. Whether these massive infrastructure bets eventually pay off financially remains genuinely uncertain, given how quickly the technology and market keep shifting. Nikkei Asia notes many of these firms are also issuing new shares to raise additional funds - but issuing new equity in this manner risks diluting existing shareholders and could gradually erode investor confidence over the coming months. Such dilution could also leave these companies even more exposed should the broader AI bubble eventually deflate or burst suddenly. Investor unease could deepen further if the industry fails to generate enough real demand to justify this data center spending spree. Notably, four of the five companies named in the investigation are scheduled to report second quarter earnings within the coming weeks. Given how much rides on these coming disclosures, markets and analysts alike will be watching each earnings report closely. Whether these tech giants ultimately resemble Enron or simply pursue an aggressive yet financially sound growth strategy remains genuinely unclear for now. Follow TechRadar on Google News and add us as a preferred source to get our expert news, reviews, and opinion in your feeds.

The growing jitters over hyperscaler debt

When they're worried, borrowers face higher borrowing costs and more difficulty getting hold of capital. The latest: Recently, a bond market credit gauge associated with Oracle hit a record high, as traders tried to grok how the arrival of low-cost, open-source Chinese AI models might change the potential profitability of providing computing capacity. * Five-year credit default swaps on Oracle -- a kind of insurance that investors can buy to protect them against a company defaulting on its debt -- jumped to 212 basis points (or 2.12 percentage points) for every $100,000 of Oracle debt to be insured. * That means it costs about $212,000 a year to insure $10 million of Oracle bonds against default. Zoom out: It's not just Oracle. * Even tech giants considered more creditworthy have seen their CDS creep higher, suggesting a relatively small but growing concern about whether they've bitten off more than they can financially chew with their capex blitz. Case in point: Apple is the exception that proves the rule. * Its CDS price is the lowest among its tech titan peers, a reflection of the fact that Wall Street has learned to love its strategic approach to AI, which rests on its dominance in devices and not spending hundreds of billions of dollars. Reality check: In the grand scheme of things, credit worries about the giant tech companies are relatively small. But they're important to watch. * The AI building boom is now highly dependent on the willingness of financial markets to fund the spending binge. What they're saying: "Credit metrics are still very strong for most of these companies," Moody's Ratings bond market analysts wrote in a report last week. "But a material shift in the structure of their balance sheets is becoming evident. While these are among the most cash-rich companies in history, the current level of spending has prompted significant borrowing." State of play: Through July 22, five companies -- Alphabet, Amazon, Meta, Microsoft and Oracle -- had raised nearly $302 billion in the markets by selling equity (creating new shares of stock) and debt (issuing bonds), according to data from S&P Global Market Intelligence. * A separate report from Goldman Sachs looked at AI-related issuance in global corporate bond and loan markets, finding "$489 billion of AI-related supply so far this year -- already well above our full-year 2025 estimate of $322 billion." Yes, but: Oracle's CDS rise suggests that at least some investors may be thinking a bit harder about the risks of such investments as new information on the scale and potential payoff from the boom emerges daily. * Nikkei published a story last week spotlighting that the major hyperscalers may have some $1.65 trillion in what the Japanese publication called "hidden debts." * These are essentially off-balance-sheet obligations -- often certain lease commitments -- which, under prevailing accounting rules, can be kept off a balance sheet. * Alphabet, meanwhile, rattled some investors by reporting its first quarter of negative free cash flow since going public in 2004, largely as a result of its rampant AI spending. What's next: Companies borrowing for AI infrastructure are likely to face rising interest costs. * In part, that's because of the credit concerns. * But even if investors had zero concern about the financial footing of these companies, borrowing costs would still be rising because of the recent increase in U.S. Treasury bond yields. The bottom line: AI buildout costs are already massive and clearly rising. Now, borrowing costs are likely to be higher as well.

After a nearly 1,000% surge, the AI debt orgy can't last forever, while hidden borrowing has exploded to $1.65 trillion | Fortune

AI's insatiable need for debt has so far been matched by investors' appetite for it, but they may turn nauseous on the belly-busting volumes coming from tech giants. The latest quarterly reports from AI hyperscalers show that their massive spending plans remain on track, with Amazon even raising its capital expenditure guidance. That means even more bond issuance is on the way after an already-staggering debt orgy. The numbers paint a picture of a borrowing binge that's bigger -- and murkier -- than it looks on paper. S&P Global counts $225 billion in bonds issued by hyperscalers and related entities like Nvidia so far this year, putting them on pace for a record haul in 2026 -- but that's just the visible debt. Other analyses suggest so-called "hidden debt" at the five U.S. tech giants has ballooned, meaning the AI boom's true price tag is only partly reflected in the bond markets that everyone's watching. Here is what is visible -- and just barely invisible -- in the hyperscalers' debt loads. 'Market participants are growing leery' S&P Global calculated that hyperscalers and "related entities" like Nvidia have issued $225 billion in bonds so far in 2026, representing a 973.7% jump through mid-year. They are on pace to issue $400 billion for the full year. But markets are showing signs of fatigue, after absorbing the flood of debt in such a short time, S&P warned, pointing out that hyperscalers are now paying a higher premium compared to yields on risk-free bonds. "Market participants are growing leery of quickly rising leverage from issuers previously characterized by strong and reliable cash flow," the report said. At the same time, the federal government also needs bond investors to scoop up all the debt coming out of the Treasury Department, with the budget deficit this fiscal year expected to hit nearly $2 trillion. And unlike earlier periods of heavy debt, the Federal Reserve is no longer a big buyer of Treasuries, placing a heavy burden on private-sector investors. Capital Economics noted that if debt trends from the first half of this year continue into the second half, then total corporate and government bond issuance as a share of GDP will be more than any year on record outside the pandemic. RSM chief economist Joseph Brusuelas said in a note last week that demand for both types of debt remains strong for now. "Yet, that will not endure indefinitely," he added Federal deficits will eventually cause lenders to charge a higher premium on public and private borrowers, Brusuelas predicted. To be sure, those yields will still attract investors looking for bigger returns, but he also cautioned against complacency. "At some point, the rivers of capital financing private and government debt issuance will flow less freely," Brusuelas wrote. Meanwhile, the official bond tally that's hitting the market understates all the actual borrowing that's going on to fund the AI boom. Explosion in hidden debt According to a study by Nikkei, so-called hidden debt at U.S. tech giants has exploded by 8x in just four years to $1.65 trillion. That amount doesn't appear on balance sheets and even exceeds the $1.35 trillion in debt that does appear on their books. These hidden debts can consist of tech companies signing long-term purchase deals for graphics processing units and servers, or lease agreements with data center operators, the report said. They are legitimate practices under accounting rules and are not totally hidden as they are often disclosed in annotations in quarterly financial statements, rather than on the balance sheet. Much of the hidden debt will also become official at some point, especially when data centers start operations. Similarly, Moody's flagged off-balance-sheet deals in a recent report, putting them at $1.2 trillion, with more than $820 billion of that attributed to data centers that are still under construction. The credit rating agency described them as debt-equivalent liabilities that will leave companies of the hook for significant rent payments in the future. Despite all the obligations, Moody's said hyperscalers still have some of the most robust balance sheets in the corporate world, and their investment-grade ratings are not facing imminent risk. Still, the tech giants are undergoing a fundamental shift, as seen by their relentless spending and borrowing. "Previously, these companies relied on asset-light structures centered on software, intellectual property, and scalable cloud services that required modest capital investment," Moody's said. "The transition from asset-light to asset-heavy models requires unprecedented levels of investment and capital raising."

AI is running on borrowed money

Wealth from Oracle, the giant tech company founded by Larry Ellison, is enabling Larry and his son, David, to become media moguls. Thanks to backing from Larry's Oracle billions, David has taken control of Paramount and is now engaged in a hotly contested $111 billion bid to take over Warner Bros. Discovery, too. They are trying to build a media behemoth containing two big movie studios, multiple streaming services and news networks CNN and CBS News, all under one enormous corporate roof. The fight over the Oracle-financed empire has, understandably, captured plenty of headlines. But what hasn't received nearly as much attention is another important development, the downgrading of Oracle debt. It now stands just one notch above junk bond status. That happened July 9, when S&P Global said that Oracle's finances had been deteriorating. Oracle has also been hit hard in the stock market, reducing the value of Larry Ellison's holdings since September by about $230 billion, according to my calculations based on FactSet data. What has damaged Oracle's debt rating and disturbed its finances is the elephant stomping throughout financial markets: colossal spending on artificial intelligence. Data centers and the other infrastructure for AI involve staggering sums of money. These cascades of AI-driven cash have enriched diverse segments of the stock market, from semiconductor makers to engineering companies to utilities to energy producers. AI money is bolstering the entire U.S. economy, contributing perhaps 1.1% to the nation's economic growth, JPMorgan Asset Management estimates. But where's that money coming from? At this point, a major source is firms like Oracle, which has gone on an immense spending spree on AI data centers, increasingly selling bonds to raise the money. Oracle is not alone. Alphabet, Microsoft, Amazon and Meta are giant investors in data centers, too. (The industry jargon is "hyperscaler.") But their underlying finances are stronger than Oracle's, and their expenditures have not landed them in the same level of trouble in the markets. Microsoft, for example, has a Triple-A credit rating -- better than the U.S. government's. Whether Microsoft manages to retain that rating after its splurges on AI data centers remains to be seen. "Microsoft is starting from a much better place, financially, than Oracle is," Mariya Entina, a portfolio manager for DoubleLine, a money management company, said in an interview. "It's important to have enough information to be able to differentiate." These five companies combined are pouring more than $800 billion into AI investments this year, and plan to add more than $1.2 trillion in 2027, according to Morgan Stanley. To put that in context, as Robert Armstrong of The Financial Times noted, the U.S. military budget request for 2027 is less than that: $961 billion, according to the Congressional Budget Office. Few people outside the markets have paid attention to what goes on behind the financial curtain for AI. These big companies are able to categorize the money as an investment -- a capital expenditure -- and not as an expense. So under current accounting rules, the bulk of the spending has not yet counted against their gaudy earnings. That is helping to propel the stock market to new heights under rosy assumptions that AI will transform the world and that the companies behind it will be making money. With the notable exception of Oracle, which has borrowed aggressively for the last couple of years, most of these companies generated so much cash from their main businesses that, until recently, their spending on AI data centers barely weighed on the performance of their stock or on the solidity of their underlying finances. But this year is turning out to be different. AI data centers are increasingly running on borrowed money. The problem goes way beyond Oracle. Hungry for Money The gigantic AI infrastructure expenditures are outpacing growth in profits. According to Bank of America, total capital expenditures for Oracle, Alphabet, Microsoft, Amazon and Meta are exceeding their free cash flow. That's the money their businesses generate beyond what they need to operate and invest in the future. The hunger for cash is likely to mount. Bank of America noted that these big tech companies, which formerly operated on relatively little invested capital, are now as capital-intensive as old-line fossil fuel companies like Exxon Mobil and Chevron. So the tech companies are going to the capital markets, mainly the bond market, which has begun to charge premiums for what it considers to be heightened risk. Oracle and Amazon bond prices have been hard hit. So have those issued by SpaceX, which is also building AI data centers. Its bonds are rated as investment grade but have been trading at fire-sale prices, like junk bonds. One problem is that the expected revenue for the data centers isn't rock-solid. Much of it is linked to AI startups like OpenAI and Anthropic, which themselves rely on borrowed funds and speculative investments by venture capitalists and private equity funds. Oracle's heavy dependence on OpenAI makes it especially vulnerable, S&P Global said. In a presentation to reporters this month, Savita Subramanian, Bank of America's chief equity strategist, drew parallels with the dot-com era of the late 1990s and early 2000s. The big "hyperscalers" have far more solid business models than many of the old internet companies did, she said, but their immense need for borrowing "is a little nerve-wracking." If their returns from AI investments don't pan out, or if their borrowing costs become onerous because of rising rates on debt, these companies may not be in an enviable position. There will be questions about whether their share pricing is "appropriate," she said, given their "leverage and capital intensity." A Great Winnowing There are signs that the markets may have started to recoil from some of the more extravagant AI bets. Four of the five big, long-established data center companies have underperformed the S&P 500 this year. Oracle has been leading the pack downward, with a fall of more than 35% through Friday. Alphabet, on the other hand, has been ahead of the market, with a stock gain of 10.8%. Alphabet's bonds are faring better, too. It may not just be that its Gemini AI model is highly rated. The company's finances are more solid than Oracle's. It has plans to raise more money through bonds -- but also through additional equity sales, which would dilute the value of existing stock shares. The stock market has so far shrugged off that move. SpaceX became a publicly traded company June 8 -- and is building big AI data centers with borrowed money. Its share price has been otherworldly, although the company has no earnings. The consensus estimate is that it will generate some next year -- but only enough to give it a price-to-earnings ratio of 182, based on its current share price, according to FactSet. That number, which measures a stock price against a company's earnings, is still off the charts: It's six times the valuation of the average company in the S&P 500. This week, SpaceX shares for the first time fell below their initial public offering price, a move that I've suggested is warranted. One day earlier, IBM's shares lost 25.2%. That was its steepest daily decline since the 1960s, and it was set off by an earnings shortfall that its CEO attributed, in part, to the spending underway on AI data centers. "We did not anticipate the magnitude of the capex reprioritization," CEO Arvind Krishna wrote in a letter to investors. Other companies spent so much money to build AI foundations, he said, that there wasn't as much left as expected for software service companies like IBM. These are early days. I have no doubt that AI is an important technology. Great fortunes are already being made. But I'm also certain that there will be many losers, as there were in two other episodes of mammoth infrastructure investments in budding technologies: the railroads in the 19th century and the various early internet companies of the dot-com era. Well-run, diversified and deep-pocketed companies have a better chance of survival in epochs like these than those that take on inordinate risk with their capital investments. Even so, the future champions may not be any of the early giants. A great winnowing is coming, and prudent investors will accept that they cannot know in advance who the winners and losers will be.

Global Market | AI boom, market correction risks emerge as major credit threats: Fitch

Ratings agency Fitch highlights AI boom and market correction as major global credit risks. Unprecedented AI spending and soaring valuations may outpace uncertain future returns, Fitch stated. Geopolitical tensions, particularly the U.S.-Iran conflict, add further significant challenges to the credit environment. Emerging markets face additional pressure from rising costs and climate-related shocks. Policymakers and investors navigate increasing dependence on AI investment amid global uncertainties. The artificial intelligence boom and the possibility of a sharp market correction have emerged as major global credit risks, ratings agency Fitch warned, highlighting concerns that soaring technology valuations and unprecedented AI-related spending may be outpacing uncertain future returns, as per a Reuters report. In its third-quarter Global Risk Outlook, Fitch said the global credit environment is facing two key near-term risks: growing vulnerability to an AI-driven market correction and continued uncertainty arising from the U.S.-Iran conflict. US MarketsPowered By As on 29 Jul 2026, 01:30 AM IST S&P 500 Top Gainers IQVIA Hldgs242.94(13.94%) Incyte129.93(9.30%) Sherwin-Williams354.27(8.25%) Workday159.69(8.24%) Gainers" S&P 500 Top Losers Corning126.01(-12.10%) Carrier Global63.16(-8.90%) Micron Technology820.53(-8.85%) Coterra Energy32.56(-8.62%) Losers" According to Reuters, Fitch's assessment comes amid rising concerns among global financial watchdogs that the AI investment cycle has become increasingly linked with economic growth and capital markets, particularly in the United States. The agency said the scale of AI-related spending has created significant exposure for economies and markets if valuations face a sharp reversal. Valuations Near Dotcom-Era Levels The warning comes as investors remain increasingly cautious about the sustainability of the AI-driven rally, with AI-linked stocks across Asia coming under pressure amid concerns over funding requirements, profitability and intensifying competition from China. Fitch noted that the cyclically adjusted price-to-earnings ratio of the U.S. S&P 500 has risen close to levels witnessed during the late-1990s dotcom boom. The agency also highlighted that U.S. corporate bond issuance jumped 26% in the first half of 2026, largely supported by fundraising linked to artificial intelligence investments. The ratings agency estimated that Amazon, Alphabet, Nvidia, Meta, Oracle and SpaceX collectively raised $182 billion through investment-grade bond issuance. Meanwhile, capital expenditure by Alphabet, Amazon, Meta and Microsoft is expected to surge more than 75% this year to $700 billion, Fitch said. Fitch estimated that strong technology investment contributed 1.4 percentage points to U.S. GDP growth in the first quarter of the year. Rising equity markets have also supported consumer spending by boosting household wealth. However, the agency warned that uncertainty around future AI revenues, regulatory changes, competitive pressures and labour-market disruptions could trigger a prolonged market correction with broader economic consequences. Geopolitical Risks Add to Credit Concerns Beyond AI-related risks, Fitch identified geopolitical tensions as another major challenge, particularly due to renewed fighting between the United States and Iran and disruptions around the Strait of Hormuz. Reuters reported that Fitch expects global economic growth to slow to 2.4% in 2026, while forecasting U.S. inflation to end the year at 3.7%, partly due to the impact of higher energy prices. The agency also flagged a strong El Niño weather pattern as an emerging credit risk, warning that droughts, floods and severe storms could worsen inflationary pressures and disrupt economic activity. Fitch said the combination of climate-related shocks and geopolitical tensions could create additional challenges for highly indebted and lower-rated economies. Rising food prices could complicate monetary policy decisions, increase government subsidy burdens and put further pressure on public finances. Emerging Markets Face Additional Pressure Fitch highlighted risks for Latin America, where higher fertiliser and diesel costs could weigh on agricultural and transport sectors. The agency noted that fertiliser and diesel account for a significant share of agricultural input costs in the region, while a substantial portion of fertiliser supplies comes from the Middle East, Reuters reported. Higher costs and weaker agricultural output could pressure agribusiness profitability and affect transport-related industries, including ports, railways and toll-road operators, Fitch warned. The ratings agency's outlook underscores the growing challenge for policymakers and investors as the global economy becomes increasingly dependent on AI-driven investment, while facing heightened geopolitical and climate-related uncertainties.

US Credit Outlook Depends on Continued Confidence Around AI: Fitch Ratings

Proposed debt issues in the second half will test market capacity to absorb new supply while equity valuations remain elevated and reliant on optimistic AI return assumptions The credit outlook for United States seems to be inexorably linked to the investor confidence around artificial intelligence (AI) at a time when the consumer-facing sectors and private credit markets appear are facing growing headwinds, says Fitch Ratings. "AI investment has become a defining driver of the U.S. economy and capital markets. IT capital spending rose 18% year-on-year in 1Q of 2026 and directly contributed 1.4 percentage points to GDP growth," the ratings agency said in a note. Increasingly debt-funded hyper-scaler capex supported a 26% year-on-year rise in U.S. corporate bond issuance in the first half of 2026, but the pipeline of planned debt and equity issuances in the second half "will test market capacity to absorb new supply while equity valuations remain elevated and reliant on optimistic AI return assumptions." Due to these factors Fitch has lowered its 2026 GDP forecast of the United States by 1.9% and no longer expects any rate cut from the Federal Reserve this year. "The policy rate is projected to remain at 3.75%. Consumer spending is forecast to slow to 1.7% as the ongoing Iran conflict and resulting fuel price shock erode real wage growth and increase affordability pressures on lower-income cohorts." On the growing household financial strain, the rating agency said, "Consumer spending is forecast to slow to 1.7% as the ongoing Iran conflict and resulting fuel price shock erode real wage growth and increase affordability pressures on lower-income cohorts." The credit rating agency further revised its year-end 2026 Consumer Price Index forecast to 3.7% and raised its benchmark US mortgage rate expectation to 6.5%, further compounding existing headwinds across housing-adjacent sectors. While the US is in the throes of a dilemma, tech giant Oracle, one of their largest investor in AI infrastructure is under pressure following S&P downgrading its credit rating earlier this month. Even its perceived credit risk has climb to its highest level in nearly 18 years amidst concerns over rising debt, heavy AI spends and growing competition from Chinese AI models. S&P lowered their long-term issuer rating credit rating (ICR) after also doing the same for its short-term commercial paper. In its note released earlier this month, the rating agency said OpenAI is estimated to make up roughly half of the $638 billion in Oracle's remaining performance obligation (RPO). "OpenAI's ability to meet its contractual obligations and raise external financing will be contingent upon AI tailwinds continuing and its models being market leaders," it said, noting that if for any reason OpenAI can't pay Oracle, they could be "left with massive datacentre leases that it might be unable to exit or have to re-lease to new tenants under less-favourable terms".

Big Tech's AI trillions: what quality of agent is actually being built? By Investing.com

Investing.com - Meta Platforms is indicated down roughly 10% in premarket trading Thursday, pointing toward $526.50, a level just above its 52-week low of $520.26, as investors challenge whether the company's massive AI capital expenditure program is producing returns that justify its scale. NVIDIA (NASDAQ:NVDA) and Palantir (NASDAQ:PLTR) are directly in the crosshairs of the same repricing: NVIDIA's credit default swaps have been rising sharply, and Palantir is indicated down about 0.87% to $121.93 in premarket trade Thursday, according to Investing.com data. Oracle (NYSE:ORCL) is adding another dimension to the pressure. The company's credit default swaps have drawn attention in credit markets as its stock has also come under heavy selling pressure, reflecting investor concern about the debt Oracle has taken on to build out its cloud and AI data-center infrastructure. Oracle has aggressively financed data-center capacity through bond issuances, and its long-term debt load has climbed sharply in recent years as it races to compete with hyperscalers. That leverage now looks precarious to credit markets if AI revenue ramps more slowly than projected. The dynamic illustrates a broader pattern across the sector: data-center debt is priced on the assumption that AI workloads will fill capacity quickly, and when that assumption wavers, credit spreads widen and equity valuations compress simultaneously. Oracle is not alone. Across the industry, companies have issued billions in corporate bonds to finance land, power agreements, and hardware -- obligations that do not shrink if enterprise AI adoption lags. The selloff is spreading globally. South Korean stocks slumped more than 9% Thursday as AI spending fears hammered chip stocks, a sign that markets are beginning to ask a harder question: what, exactly, is all this infrastructure for? The answer that keeps surfacing is not the consumer-facing AI agent that was supposed to be the payoff. It is the plumbing underneath: data ingestion, normalization, storage, and processing at scale. And the data being processed is not Gemini chats or ego-driven chatbot interactions. It is the relentless torrent of real-world signals -- location pings from phones, food delivery orders, RFID chip reads at warehouses and logistics hubs, license plate scans from Flock cameras, flight tracking data, and thousands of other streams that modern commerce and surveillance infrastructure generate every second. Big Tech's trillion-dollar buildout has cascaded well beyond GPU clusters. A recent SEC filing from renewable energy company Greenbacker Renewable Energy explicitly cites "rising data center demand" and "lack of power" as core strategic positioning pillars, illustrating how the AI capital cycle has pulled in power infrastructure financing at multiple removes from any consumer product. There is also a question that almost no one in the industry is answering publicly: how good are the agents being built on the back of all this capital? Companies are competing aggressively to acquire land, lock up power agreements, and procure GPU clusters, yet almost nothing is disclosed about the actual capability or quality of the AI systems being trained on this infrastructure. The buildout is proceeding at a scale that implies transformative results, but those results are not being demonstrated in any systematic or public way. Hundreds of billions in annual capital expenditure flows into data centers, power capacity, and chips -- and at the other end, the agents and assistants companies publicly tout remain, in most enterprise deployments, early-stage tools with narrow reliability and little independent verification of their quality. For investors, this opacity is increasingly difficult to ignore: the capital expenditure is visible and measurable; the output is not. Analysts covering Asia's semiconductor selloff have characterized it as a market repricing of AI expectations, with the central concern being whether enterprise data-collection and processing infrastructure is the actual end product being constructed, rather than the agents and assistants that companies have marketed publicly. NVIDIA sits at the pressure point of this debate. Its credit default swaps have drawn attention on Wall Street amid what analysts describe as circular financing concerns: AI companies borrow to buy NVIDIA chips, but those chips' valuations depend on continued AI investment by the very same companies. NVIDIA last traded at $190.01 on Wednesday, off more than 3.5% on the day per Investing.com data, though premarket Thursday showed a partial recovery to around $193.93. The company is scheduled to report Q2 fiscal 2027 earnings on August 26, which will be the first major opportunity for management to address whether data-center revenue growth is accelerating or plateauing and whether the circular-financing narrative has any structural merit. Palantir offers a different lens. Its core business has always been large-scale government and enterprise data integration and analytics, a mission that predates the current AI boom by more than a decade. If the broader AI buildout is effectively constructing a substrate for institutional data aggregation rather than consumer convenience, Palantir's original thesis looks less like a niche government contractor story and more like a preview of where the entire industry was heading. Oppenheimer recently reiterated its Outperform rating on Palantir ahead of the company's upcoming earnings report, a signal that the data-analytics framing remains central to how the Street values the stock. Palantir shares closed Wednesday at $123.00, per Investing.com. For investors trying to limit exposure during the current AI ETF turbulence, WarrenAI analysis published by Investing.com flagged KOMP and AIQ as offering the least risk in AI ETF selloffs, reflecting the preference for broader, less concentrated AI exposure over single-stock bets. What makes the current moment different from prior AI skepticism cycles is the breadth of the repricing. Meta's premarket move, if it holds into the regular session, would push the stock toward a test of its 52-week low. Combined with the South Korean chip rout, rising CDS spreads on NVIDIA and Oracle, and debt-market anxiety about data-center leverage across the sector, the market is no longer just questioning individual company valuations; it is questioning the architecture of the entire investment thesis. NVIDIA's August 26 earnings call will be a critical stress test of whether data-center revenue can sustain the narratives that have supported the sector's valuation through two years of aggressive capital deployment. This article was generated with the support of AI and reviewed by an editor. For more information see our T&C.