Tech giants face $1.65 trillion in hidden AI debt as investors demand returns on record spending

AI tech companies have 'hidden debt' worth around $1.65 trillion, report claims -- amount is 122% of debt reflected on the balance sheets of Alphabet, Amazon, Meta, Microsoft, and Oracle

Five U.S. tech giants heavily invested in AI and its related infrastructure reportedly have an estimated $1.65 trillion in hidden debt, with the figures annotated in their quarterly financial statements instead of being listed in their balance sheets. According to Nikkei Asia, this is higher than the $1.35 trillion officially listed, meaning investors could be caught unaware once the hidden figures come to light. The publication says that Meta has a high off-balance-sheet-to-recorded-debt ratio, with the company owing $420 billion in unlisted debts compared to the $140 billion written on the balance sheet. Oracle purportedly also has a massive $273.3 billion of hidden debt, which is a 2,900% jump from the hidden debt it had from 2022. This may sound strange, but it's actually an accepted accounting practice. The "hidden debt" stems from long-term contracts that have been signed but have not come into force yet, which, Nikkei says, is mostly related to the billions of dollars promised to data center operators. The AI race has got many hyperscalers signing contracts and agreements with data center operators, saying that they will pay for the compute they generate once their project goes online. While any institution promising to pay any amount of money for services or goods delivered is obliged to list them as a liability, the fact that these data centers haven't started operations means that these agreements are off-the-books at the moment. But when these projects come online, the contracts that the tech giants have signed will come into force, and they'll have to pay for the compute that these sites will deliver, no matter if there is demand or not. Nevertheless, these tech companies aren't just pouring money into future contracts just for the sake of it. Alphabet, Amazon, and Microsoft reportedly have a cloud service backlog worth $1.45 trillion, meaning these are services yet to be rendered and paid. Amazon Web Services CEO Matt Garman also told the publication that the investments that the company is getting into are "not speculative." While this may seem like a good way to secure capacity -- sign customer contracts that guarantee demand and then enter into long-term agreements with data centers to get the compute needed to deliver the services- it opens these tech giants to massive amounts of risk. That's because if the demand fails to materialize, then they'd be left paying for excess compute without having any customers to sell them to. What's more alarming is that Nikkei says that these investment expenditures are exceeding their earnings, meaning these big tech companies are increasingly relying on corporate bonds and new shares to fund them. Even though demand for AI compute is increasing, it's still a relatively new and unproven technology, with many experts saying that it should benefit more people to avoid a bubble. The cost of using AI for nearly everything, called "tokenmaxxing," has also caught some companies by surprise, with agentic AI eating up annual AI budgets in a matter of weeks. Because of this, some companies are reducing their use of AI or are switching to more affordable models from China. This uncertainty, paired with the way tech companies "hide" these liabilities, is quite concerning, as they would appear to have less long-term obligations than they actually do. This isn't the first time that an industry giant has used similar accounting techniques. The publication cited Enron's 2001 collapse, which was due to the company hiding its troubled assets through special purpose entities and marking unrealized gains from trading contracts into its current income statements. While the tech giants are not hiding underperforming assets off their balance sheets and committing fraud, they're still using a similar mechanism to list their upcoming obligations. Although these are technically not debt, they still behave like one, and the way they're reported is what's concerning some experts. Follow Tom's Hardware on Google News, or add us as a preferred source, to get our latest news, analysis, & reviews in your feeds.

Bond market anxiety is growing over AI capex budgets

Investors punish heavy AI spenders, while rewarding the capex-lite business models Investors are getting increasingly uncomfortable with the amount of capital needed to make the artificial intelligence buildout a reality. It's playing out in real time in the bond market, where the biggest names involved in the blitz -- Google, Amazon and Meta -- are seeing credit spreads widen as fixed-income investors demand more reward to lend to the companies. Yields ticked higher this week after Alphabet lifted its capex forecast, raising concerns that other hyperscalers could follow suit. Part of the reason capex budgets are going up is the rising cost of power. Energy is a major expense for all of the hyperscalers, which are constructing large data centers across the U.S. at breakneck speed. GE Vernova CEO Scott Strazik told CNBC he expects the current inflationary environment to remain, driven in part by the heightened geopolitical backdrop. Just this week, oil broke above $100 a barrel. The move in treasury yields is also inducing anxiety among fixed-income investors. Mizuho wrote to clients Friday morning that capex raises are testing investor limits as the companies, once seen as capital fortresses, are now seeing a dramatic rise in AI-tied costs. The analysts added that the hyperscalers are currently on track to collectively spend more on capex than they generate in free cash flow by next year. "It's creating intense discussions between bond and equity investors who have exposure to the biggest names in tech," said the portfolio manager of a credit fund, who asked to remain anonymous in order to discuss sensitive conversations.

Traders price an outsized Microsoft move as AI capex scrutiny mounts

Options traders are positioning for a swing of roughly $190 billion in Microsoft's market value after its results, an unusually large bet on a single earnings report. The pricing, reported by Reuters on 29 July, implies a move of about 6.6% in either direction once the fiscal fourth-quarter numbers land. That is well above Microsoft's own recent form. Over the past twelve quarters the options market has priced an average move of 4.8%, and the actual move has averaged 4.4%, so a 6.6% expectation signals nerves rather than routine. The figure comes from the options market, where the cost of bets that pay off on a big move translates into an implied swing. At about 6.6%, it is the market's way of saying the range of plausible outcomes is wider than usual. The nerves have a theme, and it is AI. Investors have watched Microsoft pour money into data centres and chips, and the question hanging over the print is whether that spending is translating into revenue, or simply into depreciation. The capital numbers are enormous. Microsoft's capital spending rose 49% year on year in its fiscal third quarter, to $31.9 billion, part of an industry-wide surge, from Meta's multibillion-dollar data-centre ventures on down, that has hyperscalers on track to spend more on capex than they generate in free cash flow by 2027. Azure is the number that will move the stock. Growth in Microsoft's cloud platform is the clearest proxy for whether enterprises are actually buying AI capacity, and any deceleration would feed the fear that the spending has run ahead of the demand. Guidance may matter more than the quarter itself. Investors will parse what Microsoft says about capital spending for the year ahead, since a bigger build-out promises more AI capacity but also more cost to justify before the revenue arrives. The stock has already had a hard year. Microsoft shares were down 18.7% for 2026 going into the report, even as the S&P 500 rose 8.52%, a divergence that has turned the AI trade from an assumption into an argument. The mood has shifted from faith to accounting. As one framing of the setup put it, investors have seen the AI spending and now want to see the receipts, a demand that has hardened across the megacap technology sector. Microsoft has been trimming elsewhere to fund the build-out. The company has cut jobs and restructured its Xbox operations, signs that even a firm of its size is making room on the balance sheet for the cost of AI infrastructure. The scrutiny is not only financial. Microsoft's central role in the AI boom, through its cloud and its ties to OpenAI, has drawn regulators as well as analysts, adding a layer of risk that a single earnings report cannot settle. The wider market is watching for a tell. Microsoft is among the first of the megacaps to report in this cycle, and a large move, up or down, would colour expectations for the other AI-heavy names that followed the same spend-first playbook. Whether the swing proves as violent as the options imply is unknowable in advance. What the pricing captures is the size of the disagreement, between those who think the AI build-out is a generational advantage and those who suspect it is a very expensive act of faith. The receipts arrive with the report. By the time the market reopens, Microsoft will have given its answer, and roughly $190 billion of value will have moved to whichever side of the argument the numbers support.

Microsoft earnings preview: Record AI spending, and a stock near a one-year low

Microsoft has topped earnings expectations consistently in recent years, yet its stock is near a one-year low. So while it's worth paying attention to revenue and profits when the company reports its fiscal year-end results Wednesday, there are clearly other forces at play on Wall Street. Here are the key stats and trendlines to watch going into the earnings report for the fourth quarter of the company's 2026 fiscal year, ended June 30. Core numbers: Analysts expect revenue of about $87.7 billion for the quarter, up 14.7% from a year ago, and earnings of $4.24 per share, up 16%, according to Yahoo Finance. Microsoft's own revenue guidance was $86.7 billion to $87.8 billion -- meaning Wall Street is looking for a result at the very top of the company's range. For the full fiscal year, that works out to roughly $329 billion in revenue, up 17% from $281.7 billion in fiscal 2025. Capital expense: This is the big one. Microsoft told investors to expect more than $40 billion in capital spending for the quarter, which would be a record -- up from $31.9 billion in the March quarter and $37.5 billion in the one before that. About two-thirds goes to GPUs and other short-lived hardware. For the calendar year, the company expects to spend roughly $190 billion. Chief Financial Officer Amy Hood said about $25 billion of that total is the result of higher component prices. One big question this week will be the company's guidance for capex going forward. Because this is the fiscal year-end, Wednesday brings the company's first capital spending guidance for fiscal 2027, which began July 1. Capex concerns: Google parent Alphabet last week foreshadowed what may happen to Microsoft. It reported revenue up 24% and cloud revenue up 82%, then raised its own capital spending forecast to as much as $205 billion -- well above the roughly $188 billion analysts expected. The stock fell 7% the next day and Alphabet fell below its prior $4 trillion market valuation. Big picture, investors seem to have decided the capital spending is getting ahead of the payoff. Data centers and chips cost money now, while the AI revenue meant to justify them arrives over years -- if it ever reaches the scale these companies are promising. Moody's Ratings raised its own red flags about this last week, saying the six largest cloud and AI platforms will spend about $785 billion this year and close to $1 trillion in 2027. Demand is real and accelerating, the ratings agency said, but "the ultimate return on investment is unclear." Cloud margins: This is where the capital spending starts to become evident in the company's core quarterly results. Microsoft Cloud gross margin -- the share of cloud revenue left after the cost of delivering the service -- has slipped from 72% three years ago to 66% last quarter. For the quarter it reports Wednesday, Microsoft told investors to expect about 64%. On the prior earnings call, Hood attributed the decline to AI infrastructure costs and growing use of GitHub Copilot, partly offset by efficiency gains in Azure. Microsoft doesn't absorb the cost of a data center all at once. It spreads the expense across the years the equipment is expected to last. That cost shows up here, in the expense of running the cloud -- making this one of the first places where the capital spending hits earnings. Microsoft Azure: On its prior conference call, Microsoft said it expected the Azure cloud business to grow 39% to 40% in constant currency in Q4, a slight acceleration from the 39% posted in Q3. Analysts expect roughly the same, with some outliers such as BNP Paribas looking for 41%. But the published expectations aren't the real bar. In January, Azure grew 38% -- ahead of Microsoft's guidance -- and the stock fell 10%, because Wall Street had privately been expecting 39.4%. Azure's growth rate also reflects a choice as much as it does demand. Microsoft has been routing scarce computing capacity to its own products first -- Copilot, GitHub Copilot, internal research -- and selling what remains to Azure customers. Hood has said the growth rate would have been higher had that capacity gone to customers instead. Demand continues to outrun supply, and the company expects to stay "constrained at least through 2026." Business Insider reported Sunday that the shortage of supply has pushed Microsoft to shop for additional computing capacity outside its own data centers, evaluating capacity from Amazon and Google, and that Amazon stepped in following a series of GitHub outages. Copilot and AI revenue: Microsoft said in April that its AI business had reached a $37 billion annual revenue run rate, up 123% from a year earlier. It was the first update to that number since January 2025, when the company put it at $13 billion. Whether Microsoft discloses it a third time Wednesday is a signal in itself. Microsoft 365 Copilot passed 20 million paid seats last quarter, up from 15 million in January. That's about 4.4% of the 450 million commercial seats across Microsoft 365 -- the gap that has drawn skepticism from investors all year. Microsoft said it expects the number of new paid seats to grow again this quarter. Meanwhile, the company is launching new initiatives to drive adoption of AI among its customers. Earlier this month it launched the Microsoft Frontier Company, a $2.5 billion effort to put 6,000 engineers inside customer organizations to help them deploy AI. Wednesday is also the first report since Microsoft changed how it charges for GitHub Copilot. As of June 1, customers pay based on usage rather than a flat fee per user. The OpenAI backlog: Microsoft's remaining performance obligations -- RPO, a measure of contracts customers have signed but the company has not yet fulfilled -- reached $627 billion last quarter, up 99% from a year earlier. About a quarter of that is expected to become revenue in the next 12 months. It's the strongest evidence that there's real demand supporting the AI buildout. But the RPO is also highly concentrated. In January, when it stood at $625 billion, 45% was tied to OpenAI -- roughly $281 billion committed by a single customer that is still losing money. Take OpenAI out of last quarter's figure and the growth drops from 99% to 26%. Then in April, Microsoft and OpenAI revamped their partnership, and OpenAI ended its exclusive commitment to run on Azure. Reliability: On July 23, a bug in Microsoft's automated network maintenance tooling cut a West US Azure data center off from the company's global network, knocking out Teams, SharePoint, OneDrive and Copilot Chat for about five hours. Microsoft has published a preliminary post-incident report, and a final one is due within two weeks. The outage falls in the quarter that began July 1, so it won't appear in Wednesday's numbers. But it comes as Microsoft is asking businesses to hand AI agents real control of their operations. Retirement charge: Wednesday's results will include about $900 million in one-time costs from Microsoft's voluntary retirement program, the first in the company's 51-year history. Hood said roughly $350 million falls in the cost of revenue and $550 million in operating expenses. About 8,750 U.S. employees were eligible -- 7% of Microsoft's U.S. workforce -- and about 30% accepted, Chief People Officer Amy Coleman confirmed in an interview with GeekWire, in line with what the company expected. Those departures reduced the size of the 4,800-job cut Microsoft announced July 6, which happened after this quarter ended. Even with the retirement costs, Microsoft told investors it expects operating margins for the full fiscal year to be about a point higher than last year. Hood also said on last quarter's call that headcount declined year over year and will keep declining in fiscal 2027. Windows: Microsoft expects Windows OEM revenue -- what PC makers pay to put Windows on their machines -- to decline close to 20% this quarter. A few factors are driving this: * Last year's wave of PC upgrades, when support for Windows 10 ended, makes for a tough comparison. * PC makers stocked up on parts and machines ahead of rising memory prices and are now working through them. * The PC market itself is slower, because memory prices have made computers more expensive. The memory shortage is hitting Microsoft a few different ways. In addition to adding about $25 billion to the company's capital spending this calendar year, as noted above, it lowers what Microsoft earns from Windows. Also, in late June, Microsoft raised Xbox console prices by $100 to $150, saying storage and memory costs had risen more than 2.5 times. This week: Facebook parent Meta reports the same afternoon as Microsoft, with Apple and Amazon on Thursday and Alphabet already out. Check back Wednesday afternoon for coverage.

1 hyperscaler megacap down, 3 to go. Alphabet raises the stakes on AI spending

One down, three to go. Alphabet kicked off Big Tech earnings this week -- telling Wall Street it plans to spend even more than previously expected on artificial intelligence. Now, the question is whether fellow Club names Amazon , Meta Platforms, and Microsoft will follow suit when they report next week. "Capex trends are going to be the number one focus," Club portfolio director Jeff Marks said Friday during the Morning Meeting . That's because investors are no longer giving companies a free ride on spiraling capital expenditures, increasingly demanding monetization of all their infrastructure investments -- or at least visibility towards monetization. (We explored this "AI rationalization" concept in a recent Club Check-In video .) It's also the reason why hyperscaler stock prices have hit the skids in recent weeks. On one hand, they know they have to keep spending to keep up. On the other hand, hiking capex puts pressure on their ability to generate free cash flow (FCF), a critical measure of companies' financial well-being. "They are spending because they see the demand and they don't want customers to go elsewhere," Jeff said. "But you can't ignore what it's done to free cash flow, either." GOOGL YTD mountain Alphabet YTD Alphabet tried to thread that needle Wednesday evening when it raised its 2026 capital expenditure forecast by $15 billion at the midpoint to a range of $190 billion to $205 billion and reiterated that spending will increase further in fiscal 2027. The heavier investment pushed second-quarter FCF into negative territory, with outflows of $5.8 billion. It was the first negative quarterly reading in the company's history. The capex guidance overshadowed an otherwise impressive quarter -- especially the 82% year-over-year surge in Google Cloud revenue. Even with strong cloud growth, Jim Cramer said he was not comfortable with the level of capex that the Google parent announced -- wrestling with the increasingly expensive price tag attached to that growth. Since announcing plans to sell $85 billion worth of stock to offset spending, Alphabet has been trending lower. On Thursday, the day after earnings, the stock fell 7% on Thursday, following back-to-back losses. The stock rose modestly Monday and Friday, but was tracking to become our third-worst performing stock of the week, down almost 8% over the past five days. Shares of Meta and Amazon were not much better this week, sliding nearly 7% and 6%, respectively. Microsoft stock was losing more than 2% week to date. Meta and Microsoft report earnings Wednesday evening, with Amazon out after Thursday's closing bell. Among the three, Meta may be the one to watch most closely. META YTD mountain Meta Platforms YTD The Facebook and Instagram company has already been ramping up spending to build the enormous computing infrastructure needed to support its AI ambitions. More recently, Meta has been preparing to launch a public cloud business to sell excess computing capacity to outside customers, giving another way to monetize those investments. Investors have already shown they can punish Meta when spending rises faster than expected. Last quarter, Meta increased its 2026 capital spending guidance to between $125 billion and $145 billion, a $10 billion increase at the midpoint to $135 billion, citing higher costs for memory, chips and other data center components. Shares plunged 9% following the report. At the time, Jim thought that Meta did not get the same leeway as the other hyperscalers because it didn't have a cloud. Now that cloud plans are out there, perhaps Meta might get some room to spend more. Free cash flow will be a key line item next week, though last quarter FCF increased a healthy 20% and exceeded estimates. AMZN YTD mountain Amazon YTD For Amazon, Alphabet's results likely offered the clearest justification for continued heavy spending. Google Cloud's growth and swelling backlog suggest enterprise demand for AI computing remains robust and offers an excuse to keep spending and building. That's a positive signal for Amazon Web Services, the world's largest cloud infrastructure provider. Amazon has already committed enormous sums to expanding AWS capacity, including data centers and networking equipment. Custom AI chips are also becoming more important at Amazon -- just like at Google. Last quarter , Amazon left its 2026 capex forecast unchanged at around $200 billion. We knew back in May that Amazon was projected to have negative free cash flow this year. That's why Amazon has been tapping the corporate bond market to blunt the capex impact. MSFT YTD mountain Microsoft YTD Microsoft will face a similar test with its cloud business, Azure. While operating on a different fiscal calendar than its Big Tech peers, the cloud and software giant in April laid out roughly $190 billion in expected capital spending for calendar 2026. The company's free cash flow has come under pressure in recent quarters. While the underlying demand for Azure is encouraging, as we saw with Alphabet, strong demand alone may not be enough to satisfy investors. Microsoft is one of the worst-performing megacap tech names, down 20% this year. Unlike Amazon and Google, Microsoft has major exposure to enterprise software, through its Office suite and other platforms. Software stocks have been crushed on the notion that AI could disrupt. Last month, Starbucks said it planned to drop software tools from Microsoft and IBM and use AI to make them in-house. The worry hit home more recently, after IBM preannounced a soft quarter and cut its outlook. In a bright spot, earlier this month, a Citi analyst went to bat for Microsoft's much-maligned Copilot artificial intelligence assistant. While Jim was stunned by the research, any improvement in Copilot could make Microsoft's software offerings more attractive. (Jim Cramer's Charitable Trust is long GOOGL, AMZN, META, MSFT. See here for a full list of the stocks.) As a subscriber to the CNBC Investing Club with Jim Cramer, you will receive a trade alert before Jim makes a trade. Jim waits 45 minutes after sending a trade alert before buying or selling a stock in his charitable trust's portfolio. If Jim has talked about a stock on CNBC TV, he waits 72 hours after issuing the trade alert before executing the trade. THE ABOVE INVESTING CLUB INFORMATION IS SUBJECT TO OUR TERMS AND CONDITIONS AND PRIVACY POLICY , TOGETHER WITH OUR DISCLAIMER . NO FIDUCIARY OBLIGATION OR DUTY EXISTS, OR IS CREATED, BY VIRTUE OF YOUR RECEIPT OF ANY INFORMATION PROVIDED IN CONNECTION WITH THE INVESTING CLUB. NO SPECIFIC OUTCOME OR PROFIT IS GUARANTEED.

Nadella sets a condition for the AI boom on CNN

Asked on CNN whether we are in an AI bubble, Satya Nadella did not deny it. He set a condition instead: unless AI produces broad, economy-wide growth, "we're not going to have this movie end well." That was Sunday. The same weekend, his own executives told Business Insider Microsoft is so short of compute that Copilot is served before Azure customers, even as cloud sales quotas rise 30%. Earnings land on Wednesday. Fareed Zakaria opened with the question everyone is circling. Are we in an AI bubble, and has it begun to deflate? OpenAI has promised to spend hundreds of billions while making a fraction of that, he noted. The maths does not add up. Nadella did not push back. He reframed the question as a test AI has to pass. "This is a new general-purpose technology that is going to drive productivity," he said on CNN's GPS. "That productivity has to translate into very broad-based economic growth that is economy-wide in terms of GDP growth." Then the condition. "If we don't see that, then we are going to have a problem. So unless we see that broad economic growth, we're not going to have this movie end well." It is a striking thing for the man who spent $190bn this year to say two days before his earnings call. Who gets the chips The other Nadella showed up the same weekend, in his own executives' account of the company. Microsoft cannot build capacity fast enough. The shortfall has forced it into triage, Business Insider's Ashley Stewart reported. Its own AI products eat first. Azure customers get the remainder. Chief financial officer Amy Hood said as much on January's earnings call. Microsoft solves first for M365 Copilot and GitHub Copilot, then for research and development. "Then what you end up with is the remainder going towards serving the Azure capacity that continues to grow in terms of demand," she said. Had those chips gone to Azure instead, she added, growth would have topped 40% rather than 39%. That admission is not new to readers here. A Michigan pension fund sued Microsoft in June over precisely this. The suit alleges the company hid the diversion before a January drop erased $357bn of market value. What is new is that insiders say it has got worse. "All of the supply is gone once you solve for frontier labs and our internal businesses like M365 and Microsoft AI," one executive told Business Insider. Selling what you cannot deliver Here is the part that reads oddly. Microsoft is raising quotas for its Azure salespeople despite the crunch. Some quotas rise by 30% this year, according to people familiar with the change. Meanwhile it is buying capacity from its rivals. Amazon bailed Microsoft out after a run of GitHub outages. It explored leasing Oracle cloud infrastructure and walked away over security and compliance concerns. It is now evaluating Amazon and Google. "We are shopping for capacity everywhere," one person familiar with the talks said. Inside the company, the logic is understood and the messaging is not. One executive framed the trade-off bluntly: why would Nadella prioritise growing Adobe, an Azure customer, over growing M365? "I have no idea how we're going to land that message with customers," the person added. The trap Microsoft is actually in The dilemma is real, and Microsoft is not obviously handling it wrongly. Serving Azure customers lifts revenue now. Serving its own products is a bet that they eventually win. Starve the first and Azure growth disappoints, which hits the share price immediately. Starve the second and Microsoft slips further behind in the race that justified the spending in the first place. What makes the choice urgent is that customers have somewhere else to go. Google Cloud keeps posting large numbers. Meta and SpaceX are now selling compute too. Microsoft's customers may not wait to find out what it decides. The ecosystem argument Zakaria's second question was about China. Most firms are not using AI to solve Fermat's theorem, he pointed out. They are rationalising inventory systems. So will the world simply take the cheaper Chinese open-weight models, like Moonshot's Kimi? Nadella's answer was that provenance matters less than plumbing. "Even take the Chinese models. Guess where these models run? They run on a lot of the hyperscalers that are American, all over the world." Because the weights are open, he argued, American firms can monitor, test and post-train them. If a US lab post-trains a Chinese base model and ships it, he asked, whose model is that? "As long as that remains, we will absolutely be competitive and we will win," he said. China will have a role, he added, but this is not a zero-sum game. He has been making a version of this case all week. His pinned post asks how to ensure "frontier benefits are diffused across the entire ecosystem" now that software has real marginal cost for the first time. Diffusion is the theory. Triage is the practice. Three businesses in the blast radius The strain is not only physical. Three core businesses now sit in AI's path at once. Microsoft 365 is the first. Knowledge workers used to open Word, Excel and PowerPoint to start the day. Increasingly they start inside an AI tool instead. Gartner predicted this year that AI would threaten to dethrone traditional productivity suites in a $58bn shakeup. GitHub is the second. It had its best month ever, an executive told staff. It has also suffered dozens of major outages this year as AI usage surged. Cursor and Claude Code have taken millions of engineers in the meantime. Azure is the third, and it is the one being asked to wait its turn. The billy club Nadella has pushed the pressure downwards. He has dismantled the senior leadership team structure and handed the commercial business to Judson Althoff. He also put a 33-year-old ex-Snap executive in charge of Copilot. The churn continues. Rajesh Jha has retired, Yusuf Mehdi is preparing to leave, and Charlie Bell has moved to an individual contributor role. Hayete Gallot, recruited back from Google, is seen internally as Althoff's long-term successor. Microsoft also overhauled performance reviews this year, cutting ratings to five categories and sharpening the distinctions between them. Executives say it feels like a return to the stack ranking of the Ballmer era. Managers have been told to thin out the higher-level engineering ranks. "It's almost like the old era of Microsoft is back," one former executive said. "The old Windows era where you lead with a lot of fear and a billy club in your hand." Wednesday's test Microsoft reports fourth-quarter results on Wednesday. Amazon follows on Thursday. Between them the two will spend roughly $400bn on data centres this year, Fortune reported, with Microsoft near $190bn. Investors are already twitchy. Alphabet's stock fell 7% last Thursday after it raised capital-expenditure guidance and posted negative free cash flow. Microsoft shares are down about 19% this year, and roughly 25% over twelve months. That is the worst of the Magnificent 7 by some distance. Meta is next, down almost 17%. The underlying business is not weak. Microsoft disclosed nearly $627bn of remaining performance obligations, almost double a year earlier. It is funding roughly $35bn of building a quarter from operating cash flow rather than new debt. Azure and other cloud services are forecast to reach $148.9bn in fiscal 2027. Nadella has heard doubts before. "I remember when I became CEO, everybody said, oh my God, isn't it too late man?" he recalled at a Morgan Stanley conference in March. Microsoft built anyway, and the public cloud turned out to be multiplayer. At that same conference he described the plan. "We have OpenAI book, we have Anthropic book, but we want to also have the long tail of enterprise IT," he said. The long tail is the part now waiting at the back of the queue.

AI boom's hidden $500B debt look eerily similar to the 2008 mortgage crisis

AI's explosive growth sits a massive debt structure that may blow up in our faces * Bloomberg pegs outstanding AI data center debt above $500 billion right now * CoreWeave isolates each loan inside its own separate special purpose vehicle * Parent companies report only a fraction of their real total exposure, hiding the rest in shell entities A growing body of analysts now warns that AI data center debt increasingly resembles the subprime mortgages that triggered the 2008 financial crisis. Much of that debt is issued through special purpose vehicles, structures that keep billions of dollars off corporate balance sheets entirely. Bloomberg estimates more than $500 billion in outstanding AI data center debt, with roughly $200 billion held by private credit funds. A debt structure built on theoretical revenue Special Purpose Vehicles (SPVs) raise debt to build data centers, then repay creditors only once paying customers begin generating revenue. That structure is exactly why CoreWeave has raised billions through separate SPVs for individual loans, including an $8.5 billion facility tied to Meta's contract, since each loan stays isolated inside its own entity. The same logic explains why Nikkei Asia reported that Meta, Google, Amazon, Microsoft and Oracle have accrued around $1.65 trillion in debt over five years, much of it spread across similar vehicles rather than sitting on any single balance sheet. That gap between real exposure and reported debt exists because these vehicles are jointly owned with outside investors, letting the parent company report only a fraction of the risk. Meta's Hyperion data center shows the pattern clearly: it is owned 80% by Blue Owl and only 20% by Meta itself, so the bulk of the debt lives with Blue Owl on paper even though Meta is the intended tenant. Google has used the same approach, backstopping debt-funded data centers built by Fluidstack, Cipher Mining and TeraWulf without those obligations ever touching its own balance sheet. That kind of arrangement is precisely what drew scrutiny from auditor Ernst & Young, which flagged Meta's structure as a critical audit matter, questioning who ultimately bears its economic risk. The stakes extend well beyond the companies involved, because pension funds and insurers are also directly exposed, with many now relying on data center returns to fund future payouts. Echoes of the 2008 mortgage collapse The comparison to 2008 holds up because both bubbles rested on the same flawed premise: that demand would keep growing forever and never needed to be tested. Subprime mortgages were the proof of that thinking at the time, and by 2006 roughly 20% of all new mortgages issued in the United States were already classified as subprime, according to government data. Rather than treat that as a warning sign, financial institutions bundled those loans into complex securities, a move that obscured the true underlying risk from investors and rating agencies alike. Financier Michael Milken captured the mood of the era when he publicly described such securities as a "financial innovation" that would broadly increase national prosperity and jobs. Reality caught up with that optimism once mortgage defaults began rising sharply in 2005, and the damage cascaded through the entire financial system from there. Lehman Brothers embodied how unchecked that confidence had become, operating at more than 25 times leverage in 2005 without serious pushback from regulators or rating agencies. Today's numbers echo that same pattern of unexamined risk: analysts estimate more than $1.4 trillion in bank exposure to private credit, with $300 billion of it held by major banks alone. Some estimates suggest planned AI data center capacity exceeds actual annual compute demand by a factor of roughly 15 times. Unlike 2008, this risk is not driven by derivatives but by the sheer scale of individual data center construction costs. Whether this debt unwinds gradually or all at once likely depends on how quickly major AI customers can pay their bills. For now, the scale of exposure across banks, pensions and insurers suggests the comparison to 2008 is not merely rhetorical. Via Ed Zitron Follow TechRadar on Google News and add us as a preferred source to get our expert news, reviews, and opinion in your feeds.

Amazon and Microsoft are spending $400 billion on AI -- and investors are low on patience | Fortune

The horse race between Amazon and Microsoft's cloud computing businesses has gone through various phases over its nearly two-decade history, with the current AI boom pushing the rivalry to a new, and perhaps unsustainable, level of intensity. Each company is set to spend roughly $200 billion this year building out its data centers -- an unprecedented level of investment -- in a frenzied bid to keep up with demand for AI services and to avoid getting overtaken by other cloud rivals like Google. The cloud titans have also forged partnerships and deals with the big AI model makers, creating a web of shifting alliances that each hopes could reshape the competitive landscape. This week, investors will get an important update on the state of this epic cloud rivalry, when Microsoft reports its quarterly earnings on Wednesday and Amazon follows suit on Thursday. While Amazon and Microsoft have been locked in the cloud battle for years, the pressure has never been higher and investor patience has never been more unpredictable. Revenue growth, profit margins, and customer backlogs at Amazon Web Services and Microsoft Azure will be closely scrutinized. But the costs of the race will also be destiny determinants, as investors question the massive sums of capital being deployed and the timeline for seeing a return on the investment. Last Thursday, Google parent Alphabet's stock cratered 7% after the company raised its capital-expenditure projections for the year and reported negative free cash flow in its second quarter. For Amazon and Microsoft, the two cloud computing leaders, getting an edge could hinge on who can convince investors that they can soak up all that investment and spin it into gold faster. Luke Rahbari, CEO of Equity Armor Investments who holds both stocks across several portfolios, said that even the act of raising and allocating capital has become a competitive bloodsport. "Whoever controls the money controls the winners," said Rahbari. "You've got to soak up as much money as you can so there isn't as much money available to other players." Rahbari said he'll be listening this week for signs of shakiness, and cracks in the voices of Microsoft CEO Satya Nadella and Amazon's Andy Jassy, like the kind Rahbari made "when I had to call my parents from boarding school and tell them what kind of trouble I got into." "Frenemies" Most investors are all in on both sides of the horse race. Amazon and Microsoft are two of the five largest weights in the S&P 500 with 8% to 9% of the index between them, so anyone investing for retirement has skin in the game. But the crux for any investor is that the massive spending must start flowing back to these companies as massive returns within the next few years. According to data from S&P Capital IQ, Microsoft's stock trades at about 23 times expected earnings, cheaper than Amazon's 27 times. Year-to-date, Microsoft's stock is down 19%, while Amazon has been generally flat to up 2.5%. Melissa Otto, global head of Visible Alpha research at S&P Global, described Amazon and Microsoft as competitors in a sense, but said she thinks of them more like "frenemies." The hyperscaler market between Amazon Web Services, the name of Amazon's cloud business, and Microsoft's Azure cloud business operates largely with each holding a distinct slice. In her view, AWS is the flexible, customizable platform that is ideal for startups and for enormous machine learning workloads. It's also more difficult to learn, she said. Azure extends the Microsoft software that enterprises already run, which makes it easier to adopt, she said. In sum, the two have different strengths and chase different clients. When they do go after the same cohort of companies, customers often wind up buying both, she said. The data, however, shows why it's still essentially a horse race. Between them, Microsoft and Amazon own half the cloud market, with Amazon's 28% market share topping Microsoft's 21%, according to Synergy data. Google Cloud, occupies the third spot, with its share of the market fluctuating between 12% and 14% depending on the quarter. Based on Visible Alpha consensus estimates, AWS could reach $168 billion in net sales in 2026, up from last year's $128.7 billion, a 30.7% rise. The margins AWS earns on that revenue, Otto said, "are sensational" at 93.8% gross margin, with a 35.4% operating margin expected. AWS has a current backlog of remaining performance obligations -- signed customer contracts that will bring future revenue -- of $364 billion, which excludes a recent $100 billion deal with Anthropic, Bank of America analysts wrote in a recent note, and said its in-house chip revenue commitments exceed $225 billion. Microsoft's Azure and its other cloud services are expected to reach $148.9 billion in the company's fiscal 2027, up about 40% from roughly $106 billion in fiscal 2026, which ended in June. Still, Microsoft's pace puts them slightly ahead of AWS, although it's on a somewhat lower base, said Otto. Microsoft doesn't report metrics for Azure in the same way Amazon does for AWS. Visible Alpha estimates the Intelligent Cloud business earns an operating margin of about 47%, higher than AWS's 35%. But that figure also includes older, higher-margin server software, so the actual number might be lower. Microsoft disclosed nearly $627 billion of remaining performance obligations which is 99% higher year-over-year, BofA analysts wrote. The RPO figure includes its entire commercial business, however, including Azure, M365, and Dynamics. "Not only is [the Intelligent Cloud business] very profitable, it's more profitable than AWS and growing faster," Otto said, although that edge could be because enterprises are adopting AI and spending to keep up. Still, it's anyone's game. "We're still extremely early days, so there isn't really an established winner," said Otto. "That's why it's such an arms race, because the incumbents don't want to lose their edge." Both companies are plowing cash into their businesses, buying gear and building data centers to expand their cloud and AI services. Amazon's free cash flow dropped to $1.2 billion during the past 12 months from $25.9 billion a year ago, and it more than doubled its bond debt to more than $120 billion. Microsoft isn't issuing new bonds and is instead funding a buildout of roughly $35 billion per quarter from its operating cash flow. Its free cash flow for the 12 months ending in March was $73 billion, which was actually up slightly year-over-year, though analysts say comparing the cash flow directly to AWS is complicated because of the different ways the two companies' finances are structured. The Longshot For Microsoft, the cloud race began as a longshot, as Nadella described recently. "I remember when I became CEO, everybody said, oh my God, isn't it too late man? Like, why even bother to build a public cloud because Amazon is so far ahead," Nadella recalled at a Morgan Stanley conference in March. "We knew it was going to be multiplayer. We knew that there is going to be margin, and we kept building." The building has now reached a scale that investors could never have predicted. Amazon has guided to about $200 billion in capital expenditures across the company in 2026. Microsoft spent $104 billion in the first nine months of its fiscal year 2026, and is expected to land near $190 billion for the calendar year, based on guidance from CFO Amy Hood in April. Jassy has told shareholders the AWS spending is almost all spoken for, including a commitment from OpenAI of more than $100 billion. "We're not investing approximately $200 billion in capex in 2026 on a hunch," he wrote in his annual letter to investors. "Of the AWS capex we expect to spend in 2026, much of which will be monetized in 2027-2028, we already have customer commitments for a substantial portion of it." AWS has to splash out cash on land, power, and compute about six to 24 months before it can bill customers for cloud services, he wrote. "The more capacity we open up, we sell it immediately," Matt Wood, AWS's chief AI and Technology officer told Fortune. Nadella's conviction on the massive investment rests on software, the backbone of Microsoft. Asked in March at the Morgan Stanley conference how to think about the return on all the capital Microsoft is spending, he offered a three-pronged answer that includes diverse customers, strong utilization, and a multi-generation total cost of ownership curve. "We have OpenAI book, we have Anthropic book, but we want to also have the long tail of enterprise IT," Nadella said. With both Microsoft and Amazon neck-and-neck, the two cloud businesses are are selling out of everything they can build. According to Amazon's Wood, the applications that will fund returns are still newborns. The handful of available breakout AI products include chat assistants and coding tools, much like the early days of the internet when there were only a few websites. "We're going to have millions of them, just like we have millions of websites today," said Wood. Efficiency gets customers in the door, but "there are going to be entirely new categories of products that just didn't exist a year ago that are going to be absolute breakthrough smash hits." Both companies are selling everything they can build and throwing everything they have at building as fast as they possibly can. Whether that converts into the returns investors are waiting for gets its next test this week.

AI Companies Are Trying to Hide a Staggering Amount of Debt

Can't-miss innovations from the bleeding edge of science and tech AI companies are pouring untold billions of dollars into enormous data centers in their efforts to sustain increasingly complex and resource-intensive AI models. It's an extremely costly undertaking built on seemingly bottomless hype -- and a mountain of debt. As Japanese financial newspaper Nikkei Asia found in a recent investigation, just five US tech giants -- Alphabet, Microsoft, Amazon, Meta, and Oracle -- are hiding an estimated $1.65 trillion in debt that doesn't appear on balance sheets. That's even more than the $1.35 trillion in debt the five companies officially reported in their financial data for the most recent quarter. Meta alone has amassed around $420 billion in off-balance-sheet debt, according to Nikkei, highlighting how precarious the AI industry's steep investment in AI has become, and inspiring comparisons to energy company Enron, which collapsed in spectacular fashion in 2001 because of similar debts hidden behind shell companies. Like Enron, they're using special purpose vehicles, or off-balance sheet arrangements such as legally distinct subsidiaries, as a way to make their financial reporting look healthier than it actually is -- often a glaring sign that something is deeply amiss behind the scenes. "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." Experts continue to warn of an AI bubble, noting the enormous and widening gulf between company valuations and their comparatively measly profits. The latest news will do little to quiet critics who say the situation is more dire than the companies' official balance sheets suggest. To keep up with the ongoing AI race, tech giants are committing vast sums to build out large-scale data center projects, a long-term bet that may -- or may not -- pay off. They're also selling new shares to raise new funds, as Nikkei reports, which could lead to equity dilution and a drop in investor confidence. That could make them even more vulnerable if the AI bubble does pop, or the industry fails to generate enough demand to justify the data center construction frenzy. The pressure is on: four of the five companies Nikkei analyzed are set to report second quarter earnings in the coming days and weeks. We'll be watching.

Moody's says 'unprecedented' AI spending threatens credit quality of Amazon, Meta, Alphabet and others

The race to build artificial intelligence infrastructure at a trillion-dollar annual clip is eroding the free cash flow and increasing balance-sheet risk at so-called hyperscalers, warned Moody's Ratings. In a research note released this week, Moody's said that the spending surge is forcing even the world's most cash-rich corporations like Alphabet and Microsoft to lean heavily on debt, stock sales and off-balance-sheet moves to fund their AI ambitions. "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 in the Wednesday note. "The transition from asset-light to asset-heavy models requires unprecedented levels of investment and capital raising." The moves "threaten credit quality" for the six companies tracked by Moody's, which include Microsoft, Amazon, Alphabet, Meta, Oracle and CoreWeave, according to the report. The ratings firm projects that capital expenditures -- or capex, which are investment for physical assets like data centers -- will hit $785 billion in 2026 before reaching about $1 trillion next year. The shift breaks a decades-long Silicon Valley formula that created the world's most valuable companies. Software costs little to replicate, yielding fat profit margins and fortress balance sheets. Generative AI, by contrast, demands a vast physical footprint: warehouses crammed with expensive and energy-hungry servers and chips. To finance the expansion, tech giants are increasingly turning to Wall Street, resulting in booming profits for the financial industry. Direct debt across the six hyperscalers has reached approximately $460 billion, according to Moody's. Tech companies are also tapping public markets for cash, including Google-parent Alphabet, which last month announced an $85 billion equity sale.

Big Tech earnings slam into a market in revolt over AI spending | Fortune

For years, US technology giants had a tacit agreement with investors: The companies could spend lavishly on artificial intelligence, and the stock market would reward them long as their revenues were rising. That deal is suddenly breaking down. Alphabet Inc. shares plunged more than 7% on Thursday, their worst day in over a year after the company raised its capital expenditures in 2026 to as much as $205 billion and reported that free cash flow turned negative in the second quarter for the first time since its 2004 initial public offering. Nevermind that Google's parent also delivered a whopping 82% increase in cloud-computing revenue, far surpassing Wall Street estimates. Investors were worried about all the spending. "People are really focused on capex, obsessed with it. It used to be the more the better, but now it is the less the better," said Jason Lemire, chief investment officer at Bold Wealth Partners. "We're seeing capital raises, negative cash flows, rising debt. All that adds risk to the picture." The selloff shows how much the narrative around AI and the Magnificent Seven tech behemoths has shifted. Suddenly it's become difficult to please investors as capex rises. That Alphabet got hit is particularly notable because it's seen as the biggest AI winner among the group because of the popularity of its Gemini AI services, homegrown data center chips and booming cloud-computing business. This change makes for a tough setup heading into next week, with earnings from Microsoft Corp. and Meta Platforms due on Wednesday, followed by Apple Inc. and Amazon.com Inc. on Thursday. An index tracking the Mag Seven, which also includes Nvidia Corp. and Tesla Inc., tumbled 4.8% on Thursday following the Alphabet report, its worst day since the Trump tariff "liberation day" announcement in April 2025. It's down 3.7% in 2026 after soaring for the last three years. As a result, the companies that have been dominating the S&P 500 Index since the AI boom began are increasingly ceding leadership to the recipients of the hundreds of billions of dollars they're spending, like chipmakers Micron Technology Inc. and Advanced Micro Devices Inc. Microsoft, once considered an AI leader thanks to its stake in ChatGPT owner OpenAI, is the second-weakest stock in the Mag Seven this year, plunging 21% on concerns that it's falling behind despite spending more than $190 billion on capex in the current calendar year, according to analysts' estimates. Meta shares have dropped 9.8% as investors question its own AI investments, while Amazon is basically flat for 2026. Together, Alphabet, Microsoft, Amazon and Meta are projected to pump about $724 billion into capital spending this year and nearly $950 billion in 2027, according to the average of analyst estimates compiled by Bloomberg. "We're in a period where people are inclined to sell off on capex, and Microsoft and Meta and Amazon are all holdings hands with Alphabet and jumping in to spend," said Willy Lee, principal at venture firm Neostellar Capital. "We're going to see scrutiny on all parts of their businesses as they keep spending." The investor revolt is also bringing urgency to questions surrounding the beneficiaries of all this spending, specifically chipmakers. The Philadelphia Stock Exchange Semiconductor Index, or SOX, was up 101% through the first half of the year but has lost 17% in July and is on pace for its worst month since June 2022, which was in the midst of the stock market's inflation selloff. The level of uncertainty can be seen in the 30-member chip index's recent wild swings, with volatility over the past 100 days at the highest since 2020 when the pandemic was roiling the stock market. The SOX has had 17 moves of 5% or more this year, matching the most since 2008, according to data compiled by Bloomberg. By contrast, the S&P 500 and tech-heavy Nasdaq 100 Index have had none. "There is going to be an AI winter at some point," Bold Wealth's Lemire said. "When you look at how exceptional margins are -- especially in memory -- well, it is impossible to maintain those over a long timeframe. At some point, we will see margin compression and valuation compression, and that will have a huge impact on the market." On the flipside of that trade is Apple. The iPhone maker has avoided big AI outlays, opting instead to partner with model developers to power its services. Investors have rewarded that strategy in recent weeks, sending the shares up 15% in July and putting them on pace for their best month in exactly three years. The stock has gained 23% in 2026, making it the biggest points contributor to the S&P 500's 8.3% rise. This is not say that Apple is free of problems. Soaring demand for memory chips used in AI computing have driven Apple to raise prices on products like MacBooks and iPads. How that lands with its customers and what it will mean for its profit margins remains an open question. Of course, the Mag Seven's selloff has made some of the shares relatively cheap. Microsoft, for example, is priced at 19 times estimated profits, a significant discount to its average of 27 over the past decade. Meta is priced at around 14 times compared with its 10-year average of 20. The problem is that the rush to invest in AI computing capacity is changing the companies' business models and introducing new risks. Alphabet's cash flow turning negative in the second quarter was eye opening to investors considering how much money it brings in from its various businesses. All of which has made historical valuations less relevant, according to Brad Warden, senior portfolio manager at Nomura Asset Management, whose fund holds Nvidia, Alphabet, Microsoft and Amazon. "They look cheap right now, but when you look forward at potential disruption, they are guilty until proven innocent. Is the current business model sustainable? Will economics get worse?" said Warden, who expects the AI spenders to see returns from their investments. "It really comes down to what pain you're willing to endure in an investment cycle and how strongly you believe you'll ultimately get the economics on the other end of the cycle."

Chris Wood warns of massive capital destruction in US as China challenges AI boom

Jefferies strategist Chris Wood warns that the AI infrastructure boom could trigger massive capital destruction as cheaper Chinese open-source models challenge US dominance. With hyperscalers set to spend nearly $1.6 trillion over two years, investors are increasingly questioning whether returns will justify the unprecedented capex and rising debt. Jefferies' Global Head of Equity Strategy Chris Wood has warned that hundreds of billions of dollars being poured into AI infrastructure could culminate in "massive capital destruction" as cheaper Chinese open-source models erode the economics underpinning America's investment frenzy. Wood's longer-term base case is that market share will shift towards Chinese large language models, while investors increasingly question whether US technology companies can generate adequate returns from their unprecedented capital expenditure. Microsoft, Alphabet, Amazon and Meta are expected to spend a combined $695 billion on capital expenditure in 2026, rising to $870 billion in 2027, according to figures cited in Wood's latest GREED & fear report. Together, that amounts to nearly $1.57 trillion over two years. Alphabet raised its 2026 capital expenditure guidance by another $15 billion to between $195 billion and $205 billion. Investors will now focus on the guidance from Microsoft, Amazon and Meta as they report earnings. The scale of spending has transformed businesses once known for their asset-light models. After raising their guidance in April, the four hyperscalers' estimated capital expenditure reached an "astonishingly high" 92% of their forecast operating cash flow for 2026, according to Wood. The market initially welcomed that spending, partly because surging revenue at AI companies appeared to validate demand. Anthropic's annualised revenue run rate jumped from $9 billion in December to $47 billion in May, reinforcing optimism about corporate adoption and the monetisation of agentic AI. But Wood said investors are now beginning to ask the question that had largely been deferred: where will the returns on this capital come from? Also Read | Chris Wood's big warning: The specific risk that will finally trigger the end of AI trade China challenges US dominanceThe threat from China is no longer confined to cheaper models with Wood saying that there is a growing realisation that China has become a technological peer to the US in artificial intelligence. The top Chinese AI models processed 36.39 trillion tokens on OpenRouter during the week ended July 19, compared with 7.39 trillion tokens for the leading US models. Chinese models, therefore, handled nearly five times as many tokens on the global aggregation platform. Competition intensified with the July 17 launch of Moonshot AI's open-source Kimi K3. The model was estimated to offer about 95% of the performance of Anthropic's Claude Fable 5, according to the data cited in the report. The development builds on the "DeepSeek moment" of January 2025, which first brought the cost advantage of Chinese open-source models and the associated commoditisation threat to global investors' attention. Wood's concern is that the continuing decline in token prices could prevent large language models from becoming sustainably profitable. The Silicon Data LLM Token Expenditure Index, which tracks the average price paid for one million AI tokens, has fallen 25% since its late-May peak to $1.55. Falling prices may stimulate long-term demand for computing power, but they also threaten the profitability assumptions behind the current investment cycle. Also Read | Christopher Wood warns of AI fatigue. Why Jefferies is turning to India and China AI boom acquires a credit dimensionThe risk is no longer confined to equity valuations. AI infrastructure spending has increasingly been financed with debt rather than the hyperscalers' cash, giving the boom a growing credit-market dimension. The leading hyperscalers have raised $194 billion through investment-grade debt in 2026, making them the largest single source of issuance and putting them well ahead of the US energy sector's $55 billion. Credit markets are beginning to show signs of concern. The spreads on 10-year bonds issued by Amazon, Alphabet and Meta have widened to 78, 70 and 104 basis points over US Treasuries, respectively, from 61, 57 and 87 basis points on July 3. Oracle, a more leveraged participant in the AI infrastructure race, had its $120 billion debt pile downgraded to BBB- on July 9, leaving it one notch above junk status. Its 10-year bond spread has widened from 176 basis points to 219 basis points since the downgrade. The larger vulnerability lies in the revenue backlogs being used to justify infrastructure investment. Microsoft, Alphabet, Amazon and Oracle had about $2.1 trillion of remaining performance obligations at the end of the first quarter of 2026. These represent contractual commitments for future revenue and have surged 184% from $740 billion a year earlier. About half of that backlog is owed by OpenAI and Anthropic, according to figures cited by Wood. Microsoft's backlog has about 49% exposure to the two AI companies, while the corresponding exposure is 54% for Oracle, 43% for Google and 51% for Amazon. Neither OpenAI nor Anthropic is currently profitable, although Wood said Anthropic appears more comfortably positioned. The concentration means hyperscalers have effectively extended large, unsecured commitments to cash-burning customers while building data-centre capacity on the assumption that future computing demand will materialise. The risks are even greater for specialised cloud providers that have themselves borrowed to finance chips and infrastructure. CoreWeave has borrowed about $30 billion, while its five-year credit-default-swap spread has climbed from 452 basis points in early June to 701 basis points. Hidden liabilities and flattering earningsThe balance-sheet risks may also be understated. Wood cited an estimate that the five leading US hyperscalers had accumulated $662 billion of future data-centre lease commitments that had not yet commenced, up from $152 billion at the end of 2023. A separate study put their off-balance-sheet or "hidden" debt at $1.65 trillion in the latest quarter, exceeding the roughly $1.35 trillion of debt reported on their balance sheets. At the same time, the accounting impact of the investment wave has yet to catch up fully with the expenditure. Microsoft, Amazon, Alphabet and Meta collectively spent $130 billion on capital expenditure in the first quarter, while recording depreciation and amortisation expenses of $41.6 billion. Depreciation was nevertheless 33% higher from a year earlier. Wood also flagged what he described as financial engineering in the hyperscalers' recent profit growth. Their annualised earnings increased by $106.6 billion from a year earlier to $447 billion in the four quarters through March. Other non-operating income increased by $71.5 billion to $83 billion, accounting for about two-thirds of the earnings increase. The recent earnings strength could therefore be obscuring the scale of the risks accumulating beneath the AI trade. Wood stressed that AI is not a passing story and that falling computing costs could ultimately drive much greater usage. His warning is about timing: markets may have overestimated the technology's near-term returns while underestimating the capital and credit risks required to reach its long-term potential. "The time for an extended AI hangover after the initial surge of enthusiasm is approaching, if it has not already arrived," Wood said. (Disclaimer: Recommendations, suggestions, views and opinions given by the experts are their own. These do not represent the views of Economic Times)

Big Tech Earnings Week: Can AI Spending Finally Deliver Returns? - Amazon.com (NASDAQ:AMZN), Apple (NASDA

Apple, Microsoft, Meta, Amazon Earnings: Why The Next 48 Hours Could Redefine The AI Trade This is the biggest week of Big Tech earnings season and, arguably, the most important test yet for the AI trade. With the S&P 500 hovering near record highs, simply beating revenue and earnings estimates may no longer be enough. Investors want proof that record spending on artificial intelligence is translating into stronger margins, accelerating cloud demand and sustainable cash flow. The $725 Billion Question: Is AI Spending Finally Paying Off? Wall Street's focus has shifted from how much companies are spending on AI to what they are getting in return. Amazon, Alphabet, Meta, and Microsoft are expected to spend a combined $725 billion on capital expenditures in 2026, a 77% increase from the previous year, as they continue expanding AI infrastructure and data center capacity. That spending has largely been funded through record free cash flow and debt issuance. But with financing costs remaining elevated, investors are demanding measurable returns. Meta highlighted those concerns earlier this year when it raised its 2026 capital expenditure guidance to $125 billion-$145 billion, triggering volatility as investors questioned whether spending was growing faster than future earnings. The message heading into earnings is clear: Higher AI investment must now be matched by higher profitability. 4 Big Tech Earnings Reports That Could Move The Entire Market Microsoft (Reports July 29 After Market Close) Consensus EPS: $4.21 Revenue Estimate: $64.8 billion Wall Street's biggest focus will be Azure's constant-currency revenue growth, with investors looking for growth to remain above 31%. Equally important will be management's commentary around enterprise adoption of Microsoft 365 Copilot and whether AI products are driving meaningful revenue expansion. Should Azure growth slow while infrastructure spending continues rising, investors could begin questioning whether Microsoft's AI investments are compressing margins faster than expected. Meta Platforms (Reports July 29 After Market Close) Consensus EPS: $7.18 to $7.23 Revenue Estimate: $58 to $61 billion For Meta, the key metric isn't earnings. It's capital spending guidance. The company currently expects 2026 CapEx to be between $125 billion and $145 billion, making it one of the largest investment programs in corporate history. Wall Street will closely monitor whether Meta's AI-driven advertising platform, particularly Advantage+, is generating enough revenue growth to justify those expenditures. Another increase in the Big Tech CapEx guidance, without a corresponding expansion in advertising margins, could pressure the stock despite strong headline results. Amazon (Reports July 30 After Market Close) Consensus EPS: $1.32 Revenue Estimate: $196 billion Amazon's earnings will largely hinge on the performance of Amazon Web Services (AWS). Investors are looking for stronger cloud growth alongside expanding operating margins as enterprise AI workloads continue migrating to the cloud. Any indication that AWS demand is slowing or that margins are coming under pressure could weigh not only on Amazon shares but also on sentiment across the broader AI infrastructure sector. Apple (Reports July 30 After Market Close) Consensus EPS: $1.43 Revenue Estimate: $108.9 billion Unlike its hyperscaler peers, Apple isn't being judged on cloud infrastructure spending. Instead, Big Tech investors will focus on Greater China revenue, services margins, and the company's roadmap for integrating AI features across its product ecosystem. With Apple trading at a premium valuation, any delays to AI product rollouts or continued weakness in China could become key concerns for investors. Options Markets Expect Large Post-Big Tech Earnings Moves Options traders are pricing in elevated volatility across all four reports, signaling that hundreds of billions of dollars in market value could shift during after-hours trading. Why These Earnings Matter Beyond Big Tech These reports will influence far more than the companies themselves. Microsoft, Meta, and Amazon are among the largest buyers of AI chips and data center infrastructure. Their outlooks will directly affect expectations for companies across the semiconductor supply chain, including Nvidia, AMD, Broadcom, TSMC, and ASML. Strong cloud demand and stable margins would reinforce the AI investment cycle and could reignite momentum across technology stocks. Conversely, if executives signal that AI spending is rising faster than returns -- or announce even larger capital expenditure plans without corresponding revenue growth -- the recent pullback in AI hardware stocks could deepen. The Bottom Line This week's Big Tech earnings are about more than revenue beats. Wall Street wants evidence that record AI spending is producing measurable financial returns. If Microsoft and Amazon show that cloud demand is accelerating while preserving margins, investors may view the recent technology pullback as a buying opportunity. But if capital expenditure continues climbing while profitability stalls, markets could begin reassessing the valuations that have powered the AI rally over the past two years. For investors, the next 48 hours may determine whether the AI bull market enters its next leg higher -- or its first meaningful reality check. Benzinga Disclaimer: This article is from an unpaid external contributor. It does not represent Benzinga's reporting and has not been edited for content or accuracy. Market News and Data brought to you by Benzinga APIs To add Benzinga News as your preferred source on Google, click here.

AI investment boom faces growing credit risks as hyperscalers ramp up debt: Jefferies

Investors are now scrutinising massive artificial intelligence infrastructure spending by major tech companies. Hyperscalers are increasingly relying on debt to finance these significant AI investments. Upcoming earnings reports will keep AI capital expenditure under close scrutiny by investors. Contractual commitments for AI infrastructure have significantly increased over the past year. It remains uncertain which companies will successfully monetize their AI investments long-term. The rapid expansion of artificial intelligence (AI) infrastructure is entering a new phase as investors begin to focus on rising credit risks linked to massive spending by major US technology companies, according to a Jefferies report, which said hyperscalers are increasingly relying on debt to finance AI investments while questions over future returns are beginning to intensify. The report said the upcoming earnings season for Microsoft, Amazon and Meta will keep AI capital expenditure under close scrutiny after Alphabet recently increased its 2026 capital expenditure guidance by another USD 15 billion to USD 195-205 billion. Combined capital expenditure by the four major hyperscalers is estimated at about USD 695 billion in 2026 and USD 870 billion in 2027, highlighting the scale of the AI investment cycle. "If this is the backdrop it seems to GREED & fear that the questioning of the returns on AI capex... has now begun and could well intensify in the forthcoming earnings season," the report said. According to Jefferies, one of the biggest changes in the AI investment cycle is that hyperscalers are now funding a growing share of their spending through debt rather than cash. The report said the companies have issued USD 194 billion of investment-grade debt so far this year, making them the largest issuer in the US investment-grade debt market, while bond yield spreads for companies such as Amazon, Alphabet and Meta have widened. The report also highlighted growing contractual commitments linked to AI infrastructure, noting that remaining performance obligations (RPOs) across Microsoft, Amazon, Alphabet and Oracle reached about USD 2.1 trillion at the end of the first quarter of 2026, up 184 per cent from a year earlier. It said these commitments have largely been viewed as evidence of demand supporting AI-related data centre expansion, but added that investors may increasingly examine the associated credit risks as the industry evolves. Looking ahead, Jefferies said it remains uncertain which hyperscalers will successfully monetise their AI investments over the long term. At the same time, it noted that AI remains a long-term growth theme, saying demand for computing power is expected to continue rising even if investors become more selective about the pace and financing of future AI spending.

Microsoft just took sides in AI policy fight

Every powerful technology eventually reaches the same argument. Somebody has to decide whether the thing gets handed out or locked up. Encryption had that fight in the 1990s, when the federal government classified strong cryptography as a munition and tried to keep it away from ordinary people. Software had it a decade earlier, when a small group of programmers insisted that code should be readable by anyone willing to read it. That second fight is the one worth remembering, because the side that looked reckless at the time ended up running the century. Open source software now underpins most of the internet, along with the systems that federal agencies and the U.S. military rely on every day. Nobody calls that reckless anymore. Artificial intelligence has arrived at the same intersection, and the stakes are bigger this time, because AI is not merely software. It is the thing that writes the software. For three years, America's largest AI labs have argued that their most capable models are too dangerous to hand out. Washington has been broadly sympathetic. Chinese labs have not been listening. On July 24, Microsoft (MSFT) stopped hedging and put its name at the top of a document that says the opposite. d3sign / Getty Images Why open weight AI models became a Washington problem An open weight model is one anyone can download, inspect, modify and run on their own hardware. The company that trained it gives up control the moment the file goes public. A closed model stays behind an application programming interface, or API, where the developer decides who gets access and at what price. More Artificial Intelligence: For most of the modern AI boom, the best models were closed and American. That arrangement quietly held U.S. policy together. It stopped holding on July 16, when Beijing-based Moonshot AI unveiled Kimi K3, a 2.8-trillion-parameter model it planned to release freely. One widely read estimate now puts the lag between open models and the closed frontier at roughly "3-5 months," according to Interconnects, down from the six to nine months the field had been assuming. Washington noticed. The Commerce Department had already spent June testing how far its authority reaches, imposing a license requirement on the distribution of two Anthropic frontier models before largely withdrawing it two weeks later, according to Export Compliance Daily. That episode showed the industry something uncomfortable. The government is willing to treat a model file the way it treats a weapons component. What Microsoft signed and who signed alongside it The letter is titled "Open Weights and American AI Leadership," and it lives on Microsoft's own corporate responsibility site rather than a trade group's. That placement is the tell. Microsoft is not a co-signer here so much as a host. The argument runs against the industry's own safety orthodoxy. "Relying solely on closed models is not inherently safe," the letter says, according to Microsoft, which goes on to argue that concentrating capability behind a few providers creates single points of failure. I counted 35 names on that page on the morning of July 26. The coverage on July 24reported 25. Here is how the list moved: * Twenty-five companies had signed when the letter published on July 24, including Nvidia (NVDA), Meta (META), IBM (IBM), Dell (DELL) and Palantir (PLTR), according to CNBC. * OpenAI was absent at launch, according to Tom's Hardware. * OpenAI now appears among the signatories, alongside later additions including Cisco (CSCO), Box (BOX), DoorDash (DASH) and GitHub, according to Microsoft. * Elon Musk backed the letter publicly without SpaceX (SPCX) signing it, calling it something he gave his "full support," according to CNBC. * Anthropic and Alphabet's (GOOGL) Google remain off the list. At publication, "none of the signatories sells access to a closed frontier model," according to Tom's Hardware. OpenAI's later addition complicates that reading, and it is the single most interesting thing about the document. What the open weights fight means for Microsoft stock Here is where this stops being a policy story and starts being a portfolio one. Microsoft carries a market capitalization of roughly $2.84 trillion, down about 25% over the past year, according to StockAnalysis. If you hold an S&P 500index fund in a 401(k), you own a piece of this argument whether you followed it or not. The commercial logic is not subtle. Microsoft sells cloud capacity. Every model that runs on customer-controlled infrastructure is compute Azure can rent, and Microsoft does not pay a licensing toll on weights it did not train. Closed frontier models cut the other way. They concentrate margin at the lab, which is why rivals keep building their own silicon to escape the same math, and Microsoft has been paying that toll to a partner it also competes with, as I reported for TheStreet in June. Competitors see the same incentive. U.S. labs are "clearly worried," Mozilla chief technology officer Raffi Krikorian told Axios, arguing that executives would not lobby against open weights unless they saw a genuine competitive threat. What struck me in my analysis of the signatory list is that almost nobody on it sells intelligence directly. They sell chips, clouds, tooling, distribution and security. Cheap, abundant, downloadable models make all five of those businesses larger. That does not make the argument wrong. It does mean the reader should price it as advocacy rather than testimony. Where the open weights fight heads next Three things worth watching, none of them abstract. Moonshot said it would publish K3's weights on July 27, according to Axios. That would put a near-frontier Chinese model on American laptops and force Washington to respond to a fact rather than a forecast. Microsoft reports fiscal fourth-quarter results on July 29. Azure growth has been the number that moves the stock, and a strategy built on renting compute for models Microsoft did not train is now company policy in writing. And Congress is still working through the AI Kill Switch Act, legislation that would require a shutdown mechanism for AI models. A model whose weights sit on 40,000 hard drives does not have a switch to flip. The signatories know that. They wrote the letter anyway, which tells you they would rather argue about competition now than compliance later. For everyone else, the practical read is simpler. The cost of using capable AI is heading down faster than the labs charging for it would prefer, and the companies betting on that outcome just told Washington so in public. The Arena Media Brands, LLC THESTREET is a registered trademark of TheStreet, Inc. This story was originally published July 26, 2026 at 2:36 PM.

Morgan Stanley resets Microsoft stock forecast ahead of earnings

The earnings season has kicked off with a bang, though not the kind that investors have been hoping for. Two Magnificent 7 members turned in their disappointing earnings on the same day. Alphabet (GOOGL) and Tesla (TSLA) both reported earnings on July 22, and both stocks dropped the following day. Microsoft (MSFT) and Meta (META) are next in line to report earnings on July 29. The theme for the year has already been set, when all the hyperscalers increased their capital expenditures (capex) plans as if spending more guarantees winning the AI race. The trade-off is that this serious cash burn will negatively affect free cash flow. The only Magnificent 7 members that won't have this problem are Apple (AAPL) and Nvidia (NVDA). Despite this elephant in the room, Morgan Stanley is still bullish on Microsoft. In a research note shared with me, Morgan Stanley analysts Adam Wood and Josh Baer updated their opinion on Microsoft stock ahead of the fourth quarter (Q4) earnings. Morgan Stanley believes the Q4 report will be a positive catalyst for MSFT stock Analysts said that Azure and Copilot are key drivers for the stock, and they believe that the sentiment about them is about to improve. They see approaching Q4 results as the first catalyst that will support their thesis. They noted that Q3 was strong and that Microsoft exceeded consensus estimates across all three segments, delivering approximately 1% total revenue upside, driven by 39% constant-currency Azure growth. Analysts believe that Azure growth will continue into fiscal year 2027, as Microsoft continues with its plan to approximately double its total datacenter footprint over the next two years. Wood wrote: "We believe this expanding infrastructure footprint should continue easing capacity constraints, allowing Azure to capture robust AI and cloud demand while providing further evidence that Microsoft's significant AI infrastructure investments are translating into durable revenue growth." Analysts expect Azure AI to achieve approximately 100% year-over-year growth in Q4 fiscal year 2026, or 18% quarter-over-quarter growth. They noted that Microsoft's management has said that a significant portion of capex is for longer duration assets like land and buildings, which could generate revenue for more than 15 years. Wood reiterated an overweight rating for Microsoft stock, and a price target of $600, based on a 25x multiple and EPS estimates for fiscal year 2028. He noted that this multiple represents a premium to large-cap software peers, but he believes it is justified by strong positioning and execution. Analysts noted downside risks: * Weak macro impacting IT spending * On-premises cannibalization by Cloud * Increased investments hurt margin expansion * AI adoption proves limited Upside potential: * Cloud adoption accelerates, with Azure as convincing winner * AI leadership results in substantial revenue contribution over-time * Operational efficiencies leading to greater than anticipated economies of scale and margin expansion While Morgan Stanley believes that high capex will work in Microsoft's favor, investors need to watch carefully what happens to OpenAI, as it is a major driver of that capex. Microsoft's $100 billion friendship with OpenAI is showing cracks Microsoft revised its partnership with OpenAI in April, stating that it no longer has an exclusive license for its models. It was also absent from the last OpenAI funding round. This news sounds a bit different when taken along with the amount of money Microsoft spent on OpenAI. We can thank Elon Musk's lawsuit against OpenAI for this important information. Michael Wetter, who runs the company's corporate development, testified in court that the company has spent more than $100 billion on its OpenAI investments and its costs of building data centers and hosting, according to Reuters. After spending so much money on OpenAI, it is hard to break out, and Microsoft keeps making one step forward and one step back, as we can see from what is going on with the Copilot front. Microsoft made major leadership changes to improve its AI strategy, with the most important being the naming of Jacob Andreou as EVP for Copilot. The company launched Copilot Cowork in March for Frontier (early access program), and it became generally available in June. The most recent effort was the launch of MAI-Image-2.5-Pro and MAI-Voice-2-Flash AI models, which reduce GPU usage significantly. Despite these serious efforts, OpenAI's GPT‑5.6 is the preferred model in Microsoft 365 Copilot. Not only is Microsoft competing with its partner on the model front, but it has already built and is building additional data center capacity, driven by OpenAI's insatiable demand. The problem is that OpenAI's leaked financials show it is not profitable. Tech writer and prominent AI skeptic Ed Zitron published leaked OpenAI's audited financial statements, which were verified by the Financial Times. This revealed an increase in OpenAI's net loss, from $5.09 billion in 2024 to $38.53 billion in 2025. OpenAI's way to get more investor money was to pursue an IPO, but this IPO is now in question. On July 10, Apple filed a lawsuit in a federal court in Northern California, alleging trade secret theft by former employees and OpenAI. The lawsuit could be trouble for the IPO, but OpenAI was already considering postponing it until 2027, even before the lawsuit, The New York Times reported. As if the era of tokenmaxxing ending, and OpenAI having problems, wasn't enough, Kimi K3's release only made things worse for frontier model developers. The issue here is the one that Alex Karp, Palantir (PLTR) CEO, raised, that companies are starting to realize they need more control over the models and to have security of their data. This is how these open-weight models might lead them to invest in their own infrastructure. If we add to the picture Meta entering the cloud business, which will also sell AI capacity, Microsoft could end up with excess capacity. In conclusion, Microsoft's capex might look good for Morgan Stanley analysts, but one domino falling could unravel it all. The Arena Media Brands, LLC THESTREET is a registered trademark of TheStreet, Inc. This story was originally published July 25, 2026 at 10:17 PM.

Microsoft set for US$190 billion market value swing after earnings results, options indicate

NEW YORK -- Options traders expect a roughly $190 billion swing in Microsoft's market value after it reports earnings on Wednesday, an unusually large move that underscores investors' growing eagerness to see if billions of dollars in AI spending are beginning to pay off. The tech company's options imply a move of about 6.6 per cent in either direction after the company reports fourth-quarter results. By comparison, over the last 12 earnings cycles, Microsoft has averaged a 4.8 per cent implied move and a 4.4 per cent actual move, Option Research & Technology Services (ORATS) data showed. The significantly higher pricing this quarter suggests that investors view Microsoft -- one of the hyperscalers whose massive AI capital spending is at the heart of this year's AI rally and the broader bull market -- as central to the AI earnings story. With the AI trade now faltering, investors who flocked to technology stocks are growing wary of ever-rising costs. * Latest technology news on BNNBloomberg.ca At their current trajectory, the hyperscalers are expected to spend more combined on capital expenditures than they generate in free cash flow by 2027, Reuters reported last week. "The market is looking for results," said Seth Hickle, chief investment officer at Mindset Wealth Management. "This earnings season is about AI execution, not AI enthusiasm." Microsoft's shares have fallen 18.7 per cent this year, while the S&P 500 .SPX is up 8.52 per cent. Its fiscal third-quarter capital expenditure rose 49 per cent year-over-year to $31.9 billion, down from the previous quarter's $37.5 billion. Investors will be watching whether Microsoft's AI investments are translating into stronger enterprise adoption. Beyond its Azure cloud computing platform growth, they are also eyeing whether customers are embracing Microsoft's AI tools within its ecosystem or turning to outside providers. "Investors have seen the AI spending. Now they want to see the receipts," said Peter Andersen, founder and CEO of Andersen Capital Management. "FOMO 'Fear of Missing Out' is now 'Fear of Massive Overbuilding'." INVESTORS STILL BULLISH ON SECTOR Still, many investors remain bullish. A trader spent about $10.4 million on Monday to buy 20,000 call options tied to Microsoft's stock ahead of earnings, betting the shares will rise above $450 by August, according to Chris Murphy, co-head of derivatives strategy at Susquehanna, a market maker. Calls give the buyer the right to purchase a stock at a set price by a specific date. "Investors were willing to pay high option premiums for upside exposure," said Murphy, despite recent stock underperformance, which has prompted Microsoft to cut jobs and restructure its Xbox-related business. Investors also made bullish bets on the software sector, buying 100,000 call options on the iShares Expanded Tech-Software Sector exchange-traded fund ahead of Microsoft's earnings and the Federal Reserve's meeting, reflecting confidence in both the stock and the broader software sector, Murphy said. INVESTORS ALSO WATCHING META'S AI SPENDING Meta META.O options imply a 7.8 per cent move after it reports results on Wednesday, slightly above the 7.3 per cent average implied move over the last 12 earnings cycles, according to ORATS data. Historically, Meta's stock tends to move slightly more than options markets anticipate, averaging 7.9 per cent. Matt Amberson, founder of ORATS, said earnings-related volatility has increased over the past year, with particularly large reactions in the last three quarters. Investors will focus on the strength of Meta's core advertising business, the impact of AI on engagement and advertising efficiency, and whether the returns from its expanding infrastructure investments can justify the level of spending, said Matthew Smart, chief investment officer at WWM Investments.

Microsoft Q4 Earnings: Can $220B in AI Investment Cement Azure's Cloud Dominance?

Microsoft (MSFT) reports fiscal Q4 2026 results later this evening for its fiscal year-end, and will issue FY2027 guidance, the key number the AI trade is watching. Analysts expect EPS of about $4.21-$4.24 and revenue near $87.7B, up roughly 15% year-over-year for both extending a four-quarter streak of beats. Key Highlights * Microsoft (MSFT) posted strong Q3 FY2026 results: revenue rose 18% YoY to $82.9B and EPS grew 23%, driven by Microsoft Cloud up 29% to $54.5B. Azure and AI infrastructure investments are fueling demand, making cloud and AI core growth engines, though macro uncertainty and higher capex create supply-demand pressure. * MSFT trades 29% below its 52-week high of $555.45, at about 20.6x forward earnings -- one of its cheapest multiples in years despite continued double-digit revenue growth. * Today's report closes fiscal 2026 and must include guidance for FY2027. Consensus revenue $87.7B (+14.7% YoY) and EPS $4.22 (+15.6%). The key is Amy Hood's capex outlook. If she guides around $220B (20-30% growth), it'll look disciplined vs. Azure's pace; a higher figure would fuel concerns the spending has no ceiling. * A key focus this week is capex guidance, as fiscal year-end, brings Microsoft's first FY2027 capital-spending outlook (fiscal year began July 1). Key items to watch in Microsoft's fiscal Q4 results * Azure guidance: Azure has surged but faces capacity limits. Management is guiding 39-40% constant-currency growth this quarter, the single most important metric and we'll watch commentary on how much capacity is reserved for internal use and any details on Azure's recovery point objective. * AI: Microsoft's AI-driven capex has outpaced revenue, raising questions about payback on these investments. Look for updates on Claude Copilot seat growth (software licensing) and whether it's accelerating enterprise AI adoption. * Margins: Margins should hold, but rising capex means depreciation could increase materially -- a key risk to monitor. * Copilot and AI revenue: Microsoft said in April its AI business reached a $37B annual run rate (up 123% YoY), versus $13B in Jan 2025. Whether management updates that figure again on Wednesday will be a key signal. Analysts Expectation * Scotiabank cut its MSFT price target to $470 (from $550) but kept a Sector Outperform rating. * Citizens reiterated a Market Outperform rating and $550 price target for Microsoft (MSFT). * Piper Sandler analysts reiterated an Overweight rating and $540.00 price target on Microsoft (MSFT). MSFT Q4 2026 earnings after market (4:05 pm ET) Wednesday July 29, 2026 Expected Move by Option Expiration Options traders price a roughly $190B swing after Wednesday's earnings, highlighting investors' eagerness to see if massive AI spending is paying off. Options market imply about a 6.9% move after Q4 results, roughly up to $420 or down to $366.05 by Friday versus a 12-cycle average implied move of 4.8% and actual move of 4.4%, ORATS data show. The put/call ratio is tilted toward calls across the next four expirations. Technical Analysis Perspective * MSFT formed a double-top near the $555 highs (July & Oct 2025). * Stock found support at $355-$345 in Apr 2025, Mar 2026 and late June, prompting strong rebounds. * The current rebound becomes a triple-bottom bullish setup if price clears and holds above $405-$408 after earnings. * A confirmed break above $405-$408 would target $442-$455. * Base case: break and hold above $405-$408 → rally to $442-$455. * Alternate case: rejection at $405-$408 → pullback to the $355-$345 base. Weekly Candlestick Chart MSFT Seasonality Chart: Since 2007, MSFT closed July, higher 65% of the time (avg +2.59%) and August higher 58% of the time (avg +1.41%). *** Ali Merchant is a seasoned financial market professional with expertise in Technical Analysis, Treasury & Capital Markets, Trading, Sales, Research, Training, & Fund Management. He is the founder of www.twtlearning.com providing financial education, research and advisory services to fund & hedge fund managers and family offices. He has been trading FX, FX options, US stocks & options, Indices, Commodities & Oil, and Metals Futures. He has a CMT charter, an AAPTA membership, and a CMT Canada membership. He has worked in various roles and organizations in North America and the GCC, such as ABN Amro bank, Thomson Reuters, Refinitiv, MAK Allen & Day Capital Partners, and Bridge Information Systems. He is regarded as an excellent mentor and has trained more than 2000+ users in North America, Gulf countries & Asia on financial markets & products, active and passive trading, and technical analysis strategies. He emanated technical analysis daily and weekly reports for BridgeNews Chicago bureau and updated technical analysis reports on Bloomberg and Reuters while working with ABN Amro bank treasury & capital markets. Has moderated and produced technical analysis reports for Thomson Reuters (Refinitiv) users' chat rooms and trained users on technical analysis techniques and models. Conducted TA & Global Markets outlook workshop with central banks, sovereign funds, global & regional banks & family offices.

Wall Street's AI trade faces its biggest valuation test

Alphabet just reported the strongest quarter in Google Cloud's history. Revenue came in at $119.8 billion, up 24% year over year. Cloud grew 82% to $24.8 billion and blew past analyst estimates. The Cloud backlog hit $514 billion. Nearly 90% of the Fortune 100 is using Gemini Enterprise. By most definitions, that is a blowout quarter. The stock fell 6.5% the next morning. Capital expenditures came in at $44.9 billion for a single quarter. Free cash flow turned negative. Most of the net income surge came from a one-time gain on the Anthropic stake. Strip that out and investors were left looking at a company spending at a rate that makes even strong revenue growth feel like it may not be enough. Microsoft (MSFT) reports July 29 and Meta reports July 30. The next week is effectively a live test of whether the AI trade's math actually works. What Alphabet's Q2 results reveal about the AI trade's biggest risk The Alphabet (GOOGL) reaction captures the problem in one quarter. Cloud revenue grew faster than at any point in the company's history. Investors sold the stock anyway, CNBC reported. The issue isn't whether AI is generating revenue. It's whether the capital required to generate that revenue is sustainable, and whether the returns will ever justify the scale of investment. Forty-four billion dollars in quarterly capex is not a small number. Annualized, that's close to $180 billion from Alphabet alone. When you add Microsoft, Meta (META), and Amazon (AMZN), the combined spending for 2026 is running toward $725 billion, with analysts projecting it could cross $1 trillion in 2027, CNBC reported. The question the market is now pricing into every print is how long before the revenue catches up, as TheStreet reported ahead of Alphabet's earnings. The gap between AI spending and AI revenue that investors are watching The capex-to-revenue gap is the central tension in the AI trade right now. Sequoia analyst David Cahn has calculated that there is roughly a $600 billion annual gap between what hyperscalers are spending on AI infrastructure and what the AI ecosystem generates in actual sales, Forbes reported. Goldman Sachs has noted that to justify the scale of investment, hyperscalers would collectively need to generate more than $1 trillion in annual profits, more than double current consensus estimates, as TheStreet reported. According to Allianz Research, the divergence between AI capital spending and revenue growth is running at 46%, already wider than the 32% divergence seen during the 2001 telecom cycle that preceded years of pain in tech stocks. Michael Heinrich, co-founder and CEO of 0G Labs, which builds decentralized AI infrastructure, described the dynamic plainly in an interview with TheStreet: "When the capital going into a technology outruns the revenue coming out of it by that margin, valuations are pricing perfection." Alphabet's results were exceptional. And still, free cash flow went negative. That's what "pricing perfection" looks like in practice: a quarter that would have been a strong earnings beat in any other sector, and a stock that still dropped because the bar for AI spending to produce proportional returns keeps moving higher. How the AI rally compares to the dot-com era and where it diverges The comparison to the late 1990s is now coming from serious voices. JPMorgan CEO Jamie Dimon said earlier this month that AI spending may not "pay off the way you expect and the timetable you expect." He drew a direct parallel to the internet boom, where the technology proved transformative but the timeline disappointed nearly everyone who priced it in early. Heinrich sees both the parallel and where it breaks. "The similarity is the reflexive bidding up of anything with the label attached, well ahead of proven business models. The difference is that the underlying technology this time is already generating real usage and real cash flows, so this is less a fiction problem and more a physics and economics problem," he added. The dot-com era was full of companies with no path to revenue. AI has actual enterprise customers paying for actual products. Google Cloud at 82% growth is not a fiction. The risk isn't that the technology doesn't work. It's that the cost of delivering it at scale may not produce returns proportional to the capital being committed, at the speed the market has priced in. What Microsoft and Meta need to show for the AI test to pass Microsoft's July 29 report will be the next data point. Azure guided for 39% to 40% growth in constant currency. If it delivers at or above that, the market will read it as confirmation that cloud AI spending is translating into revenue acceleration. If it misses, questions about the return on $190 billion in annual capex get louder fast, as TheStreet reported. Meta reports July 30 against its own complicated backdrop. The company has already cut 8,000 jobs this year and moved thousands of employees into AI roles, then acknowledged at an internal meeting that AI-agent progress has not accelerated as expected. The question on Meta's call is whether $125 billion to $145 billion in AI spending this year is producing the kind of product traction that justifies it. Three things will tell investors whether the AI trade is facing a healthy correction or something more serious: * Whether the gap between AI infrastructure spending and AI revenue is narrowing; * If AI is moving from assistant to agent, meaning systems that complete tasks and get paid for outcomes rather than just answering questions, and * Whether the unit economics of running AI inference are falling fast enough to make applications viable at scale. The next two earnings reports will give investors more data on all three than any single quarter has provided yet. The Arena Media Brands, LLC THESTREET is a registered trademark of TheStreet, Inc. This story was originally published July 24, 2026 at 11:03 AM.

Big Tech Didn't Just Overspend on AI -- The Question Is by How Much

Some ask whether or not big tech overspent. I ask by how much. The Wall Street Journal asks Will Someone Finally Blink in the AI Spending War? Big tech reining in its AI spending may be a tantalizing prospect for some. It would also be a costly one. That doesn't seem in the cards yet. Second-quarter reports coming later this month will likely show another period of blowout AI investments. Wall Street analysts estimate that combined capital spending by Google, Microsoft , Amazon and Meta Platforms year over year to hit $168 billion in the June-ending quarter, according to consensus estimates from Visible Alpha. This spending is crimping both the free cash flow and stock prices of those four companies; only Google-parent Alphabet has managed to outperform the S&P 500 this year. But there are also some signs that AI's big spenders are looking for more ways to at least rationalize their investments. Before SpaceX went public last month, its xAI business signed a major deal to effectively share its computing capacity with Anthropic -- for $1.25 billion a month. Now Meta may be getting in on that action. Bloomberg reported last week that the social-network giant is developing a cloud-computing business using the extensive AI network it has built out. Meta would be very late to that industry; Amazon, Microsoft and Google have all been selling cloud services to businesses for well over a decade. But Bernstein Research analyst Madison Rezaei says the scale of Meta's network already "easily rivals cloud provider footprints." She estimates the company has about 20 gigawatts of computing capacity now with an additional 14GW coming online over the next few years. Renting out some of that capacity would effectively confirm that Meta has overshot in its build-out. Founder and Chief Executive Mark Zuckerberg said as much at the company's annual shareholder meeting in late May. "We haven't done that yet because we think that we have a use for the compute," Zuckerberg said, in response to an investor's question about building a cloud service. "But obviously, if we get to a point where we feel that we have overbuilt, then that is an option that we have." The big question would be whether renting out excess capacity is a short-term offset to continued mega-spending, or a sign that such spending is about to recede. Meta is a smaller company than Amazon, Microsoft and Google, but it has been the most ambitious in its AI investments. Zuckerberg has built up a division called Meta Superintelligence Labs in a push for the social network to be the first to develop a supercharged form of AI. Meta expects to spend well over half its revenue this year on capital investments, which will likely take its free cash flow into negative territory for the first time in its life as a public company. Most analysts doubt that Meta plans to actually scale back its spending. "Meta is not stepping away from the AI race; it is turning early, aggressive capacity commitments into a strategic value creation option," wrote Brent Thill of Jefferies. Still, the idea that the company has excess capacity at this stage of its AI cycle raises eyebrows. Justin Patterson of KeyBanc Capital said "it is conceivable that the scope of MSL's ambitions have narrowed vs. Meta's original AI goals when it began the capex cycle." Big Tech's Financials Obscure True Cost of AI Buildout The above link is a free WSJ link. The article has a related video that worth watching on the true cost of the ai buildout. Here's a stat that caught my eye. 90 percent of stock buybacks have gone to stock options for employees. The competition for top AI recruits has been so intense that the big tech companies have been using free cash flow to hire employees masking shareholders dilution. Free cash flow estimates are essentially a huge lie. It's a fascinating video well worth a play. It explains how and why companies get away with this. And none of it is illegal. Circular Financing Nvidia is facing scrutiny over allegations of employing "circular financing" (or "round-tripping"), where the company allegedly invests in or lends money to AI startups and cloud providers (e.g., OpenAI, CoreWeave), which then use those funds to purchase Nvidia's GPUs. Analysts worry this creates artificial revenue growth and inflates AI demand. So not only has AI overbuilt capacity, free cash flow is very overstated as well. $1.8 Trillion in Off-Balance Sheet AI Risk Also note $1.8 Trillion in Off-Balance Sheet AI Risk Reminiscent of Enron There's $1.8 trillion in AI-related debt off the balance sheets vs $1.4 trillion on. The hardware makers and cloud providers post massive revenues. However, the pure-play AI developers like OpenAI and Anthropic are operating at a significant loss as they burn billions on infrastructure to build and run their models. That money is fueling profits at the chipmakers. But most of the risk is hidden off the balance sheet, inflating earnings. How long this can go on is unknown but cracks are clearly visible now.

The AI Buildout Is Not Overbuilt -- It Is Becoming an Asset Class

The Economics of AI Across Three Layers: * The hardware layer: generational transfer in free cash flow is underway * The hyperscalers: compute is becoming an asset class, not a sunk cost. * The labs: the first profitable frontier lab is about to reprice the whole stack This week Alphabet printed its first negative free cash flow since it went public. Anthropic signed its fourth chip deal in nine months. Meta all but confirmed it will rent out compute. So we are stepping back to map the economics of the AI buildout and highlight where we are finding opportunities. Our lens is simple: follow the cash through the hardware layer, the hyperscalers, and the labs. The picture is far more constructive than the "capex-is-out-of-control" headlines suggest. 1. The Hardware Layer: A Generational Transfer in Free Cash Flow Combined 2026 hyperscaler capex has reached ~$725B, up ~77% from ~$410B in 2025, and our work points to more than $1 trillion in 2027. That spending thus far has been coming from operating cash flow, but things are changing. Alphabet just posted its first negative FCF since its 2004 IPO. At the same time, this is landing as record profitability one layer down, where memory pricing is up a cumulative 435% and Micron's gross margins are nearing 86%. Compute alone is a ~$380B line this year, roughly double 2025. The read-through is broadening well beyond Nvidia. Intel's data-center revenue grew 59% (its best in 15 years) and Texas Instruments' data-center sales are set to double past $3B, while custom silicon pulls a much wider ecosystem (memory, CPUs, networking, packaging) along with it. When the hyperscalers guide capex up, they guide demand up for all of them. We continue to see the hardware layer as the best risk-reward in the sector. 2. The Hyperscalers: The Compute-Resale Opportunity The new bear case is that "compute scarcity is over," pointing to two of the biggest buyers: SpaceX and Meta turning into sellers. The deal economics say otherwise. On our math, a gigawatt costing ~$30B to build throws off ~$14.5B of net income a year at conservative rental rates, a ~2-year payback. Meta sits on ~7GW, doubling to ~14GW, at an estimated 60-70% utilization; monetizing ~5GW of excess could add ~$70B of income. That is not overbuilding; it is compute becoming an asset class. The depreciation scare fails the same test: four-year-old GPUs still command rising rental rates, so the "worth zero in year five" assumption behind the bear case doesn't survive contact with the resale market. And demand is contracted. More than $2T of backlog sits across the big four clouds. Alphabet is the cleanest expression: Cloud grew 82% to $24.8B at a 36% margin on a $514B backlog, still short of capacity even after guiding capex to ~$200B, while turning its own TPUs into a revenue stream with Anthropic and Meta. The clearest proof landed this week. Anthropic contracted more than 11GW of compute across four deals, and three of the four are with hyperscalers: Google, AWS and Azure. For the hyperscalers, renting compute to the labs isn't a sign of a glut. It's the second monetization engine coming online. With capex now outrunning cash flow, funded increasingly by debt, equity and off-balance-sheet leases, access to capital and credit quality is itself becoming the moat. The Labs: The P&L Behind the Anthropic IPO The labs are where demand originates and where the "does it pay?" question gets answered. Anthropic's run rate has gone from ~$9B at end-2025 to more than $47B by mid-2026, roughly 80x in a year. Our token-economics work explains why its expected October listing reprices the whole cycle: inference cost has fallen ~40x since early 2024 while revenue per token fell only ~9x, swinging quarterly gross profit from -$55M to an estimated $1B+ by 3Q26 -- the first profitable frontier lab. Anthropic's four chip deals across Google, AWS, Microsoft/Nvidia and AMD total more than 11 gigawatts, with the vendors funding their own buyer. The economics need only a sliver: at list pricing, monetizing under 1% of a single 2GW deployment supports ~$30B of revenue, and our enterprise work shows token consumption still early on its S-curve. Anthropic economics become the guidepost for the entire stack. Bottom Line Where we're finding opportunities. Follow the cash and the same answer surfaces: the hardware layer offers the cleanest risk-reward as free cash flow shifts from buyers to suppliers. The market keeps hunting for the peak. The economics keep pointing higher-for-longer.