The billion-dollar infrastructure deals powering the AI boom

4:36 AM IST · March 1, 2026

It takes a lot of computing power to run an AI product — and as the tech industry races to tap the power of AI models, there’s a parallel race underway to build the infrastructure that will power them. On arecent earnings call, Nvidia CEO Jensen Huang estimated that between $3 trillion and $4 trillion will be spent on AI infrastructure by the end of the decade — with much of that money coming from AI companies. Along the way, they’re placing immense strain on power grids and pushing the industry’s building capacity to its limit. Below, we’ve laid out everything we know about the biggest AI infrastructure projects, including major spending from Meta, Oracle, Microsoft, Google, and OpenAI. We’ll keep it updated as the boom continues and the numbers climb even higher. This is arguably the deal that kicked off the whole contemporary AI boom:In 2019, Microsoft made a $1 billion investment in a buzzy non-profit called OpenAI, known mostly for its association with Elon Musk. Crucially, the deal made Microsoft the exclusive cloud provider for OpenAI — and as the demands of model training became more intense, more of Microsoft’s investment started to comein the form of Azure cloud creditrather than cash. It was a great deal for both sides: Microsoft was able to claim more Azure sales, and OpenAI got more money for its biggest single expense. In the years that followed, Microsoft would build its investment up to nearly $14 billion — a move that is set to pay off enormously when OpenAI converts into a for-profit company. The partnership between the two companies has unwound more recently. Last year, OpenAI announced it wouldno longer be using Microsoft’s cloud exclusively, instead giving the company a right of first refusal on future infrastructure demands but pursuing others if Azure couldn’t meet their needs. Microsoft has also begun exploring other foundation models to power its AI products, establishing even more independence from the AI giant. OpenAI’s arrangement with Microsoft was so successful that it’s become a common practice for AI services to sign on with a particular cloud provider. Anthropic has received $8 billion in investment from Amazon, whilemaking kernel-level modificationson the company’s hardware to make it better suited for AI training. Google Cloud has also signed onsmaller AI companies like Lovable and Windsurfas “primary computing partners,” although those deals did not involve any investment. And even OpenAI has gone back to the well, receiving a $100 billion investment from Nvidiain September, giving it capacity to buy even more of the company’s GPUs. On June 30, 2025, Oracle revealed in an SEC filing that it had signed a $30 billion cloud services deal with an unnamed partner; this is more than the company’s cloud revenues for all of the previous fiscal year. OpenAI was eventually revealed as the partner, securing Oraclea spot alongside Googleas one of OpenAI’s string of post-Microsoft hosting partners. Unsurprisingly, the company’s stock went shooting up. A few months later, it happened again.On September 10, Oracle revealed a five-year, $300 billion deal for compute power, set to begin in 2027. Oracle’s stockclimbed even higher, briefly making founder Larry Ellison the richest man in the world. The sheer scale of the deal is stunning: OpenAI does not have $300 billion to spend, so the figure presumes immense growth for both companies, and more than a little faith. But before a single dollar is spent, the deal has already cemented Oracle as one of the leading AI infrastructure providers — and a financial force to be reckoned with. As AI labs scramble to build infrastructure, they’re mostly buying GPUs from one company: Nvidia. That trade has made Nvidia flush with cash — and it’s been investing that cash back into the industry in increasingly unconventional ways. In September 2025, Nvidia boughta 4% stake in rival Intelfor $5 billion — but even more surprising has been the deals with its own customers. One week after the Intel deal was revealed, the company announceda $100 billion investment in OpenAI, paid for with GPUs that would be used in OpenAI’s ongoing data center projects. Nvidia has since announced a similar deal with Elon Musk’s xAI, and OpenAI launcheda separate GPU-for-stock arrangementwith AMD. If that seems circular, it’s because it is. Nvidia’s GPUs are valuable because they’re so scarce — and by trading them directly into an ever-inflating data center scheme, Nvidia is making sure they stay that way. You could say the same thing about OpenAI’s privately held stock, which is all the more valuable because it can’t be obtained through public markets. For now, OpenAI and Nvidia are riding high and nobody seems too worried — but if the momentum starts to flag, this sort of arrangement will get a lot more scrutiny. For companies like Meta that already havesignificant legacy infrastructure, the story is more complicated — although equally expensive. Meta CEO Mark Zuckerberg has said that the company plans to spend $600 billion on U.S. infrastructurethrough the end of 2028. In the first half of 2025, the company spent$30 billion morethan the previous year, driven largely by the company’s growing AI ambitions. Some of that spending goes toward big ticket cloud contracts, like a recent$10 billion deal with Google Cloud, but even more resources are being poured into two massive new data centers. A new 2,250-acre site in Louisiana,dubbed Hyperion, will cost an estimated $10 billion to build out andprovide an estimated 5 gigawatts of compute power. Notably, the site includes an arrangement with a local nuclear power plant to handle the increased energy load. A smaller site in Ohio, called Prometheus, is expected to come online in 2026, powered by natural gas. That kind of buildout comes with real environmental costs. Elon Musk’s xAI built its own hybrid data center and power-generation plant in South Memphis, Tennessee. The plant has quickly become one of the county’s largest emitters of smog-producing chemicals, thanks to a string of natural gas turbines thatexperts say violate the Clean Air Act. Just two days after his second inauguration last January, President Trump announced a joint venture between SoftBank, OpenAI, and Oracle, meant to spend $500 billion building AI infrastructure in the United States. Named “Stargate” after the 1994 film, the project arrived with incredible amounts of hype, with Trump calling it “the largest AI infrastructure project in history.” OpenAI’s Sam Altman seemed to agree, saying, ”I think this will be the most important project of this era.” In broad strokes, the plan was for SoftBank to provide the funding, with Oracle handling the buildout with input from OpenAI. Overseeing it all was Trump, who promised to clear away any regulatory hurdles that might slow down the build. But there were doubts from the beginning, including from Elon Musk, Altman’s business rival, who claimed the project did not have the available funds. As the hype has died down, the project has lost some momentum.In August, Bloomberg reported that the partners were failing to reach consensus. Nonetheless, the project has moved forward with the construction ofeight data centers in Abilene, Texas, with construction on the final building set to be finished by the end of 2026. “Capital expenditures” are usually a pretty dry metric, referring to a company’s spending on physical assets. But as tech companies lined up to report their capex plans for 2026, the rush of data center spendingmade the figures a lot more interesting— and a lot bigger. Amazon was the capex leader, projecting $200 billion in 2026 spending (up from $131 billion in 2025), while Google was a close second with an estimate between $175 billion and $185 billion (up from $91 billion in 2025). Meta estimated $115 billion to $135 billion (up from $71 billion the previous year), although that figure is a little deceptive because a lot of the data center projects have beenkept off their books entirely. All told, hyperscalers are planning to spendnearly $700 billion on data center projects in 2026 alone. It was enough money to spook some investors. The companies were mostly undeterred, however, explaining that AI infrastructure was vital to their companies’ future. It’s set up a strange dynamic. As you might expect, tech executives are more bullish on AI than their Wall Street counterparts — and the more tech companies spend, the more nervous their bankers get. Add in thehuge amounts of debtmany companies are taking on to fund those buildouts, and you start to hear CFOs across the valley grinding their teeth. That hasn’t put a damper on AI spending yet, but it will soon — unless of course, hyperscalers show they can make those investments pay off. This article was first published on September 22.

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Medicare’s new payment model is built for AI, and most of the tech world has no idea

Neil Batlivala has spent seven years building a healthcare company that most of the tech industry has never heard of and that serves a patient population most of Silicon Valley ignores. But last month, that work put him at the center of something much bigger. His company,Pair Team, announced on April 30 it had beenacceptedintoACCESS, a Medicare program — as one of 150 participants chosen by the Centers for Medicare & Medicaid Services to test what AI-driven medical care could look like at federal scale. The program goes live July 5. “The government is creating swim lanes for AI innovation in traditionally regulated industries,” he told me over a Zoom call a few days later. “The best solution wins, which, in regulated industries like healthcare — that’s not been the case.” ACCESS — Advancing Chronic Care with Effective, Scalable Solutions — is a 10-year CMS program testing a payment model that rewards health outcomes rather than required activities (like a certain number of check-ins). Participating organizations like Pair Team receive predictable payments for managing qualifying conditions and earn the full amount only when patients meet measurable health goals, like lower blood pressure or reduced pain. It covers diabetes, hypertension, chronic kidney disease, obesity, depression, and anxiety. That payment structure is the real news. Traditional Medicare reimburses based on time spent with a clinician. There’s no mechanism to pay for an AI agent that monitors a patient between visits, calls to check in, coordinates a housing referral, or makes sure someone picks up their medication. ACCESS creates that mechanism for the first time. “It’s a payment model transformation,” Batlivala said. “You just couldn’t do this before.” The first cohort spans a wide range of participants — AI doctor startups, virtual nutrition therapy providers, connected device companies, and wearable makers like Whoop. Batlivala is skeptical of some of them. "I'm a big fan of wearables, but for a senior who's struggling with food insecurity, I don't know how much Whoop is going to be able to do," he said, adding of his own company, "We've been building toward this for five-plus years now." Pair Team launched in 2019 with a specific kind of patient in mind: people managing chronic conditions who were also dealing with unstable housing, too little food, or lack of transportation. About a third of Americans fall somewhere in that category. The company's premise was that you can't improve health outcomes without addressing the full context of someone's life. It now employs roughly 850 clinical professionals, runs what it describes as the largest community health workforce in California, and, per Batlivala, generates revenue above nine figures. It has raised about $30 million, backed by Kleiner Perkins, Kraft Ventures, and Next Ventures. The model has peer-reviewed evidence behind it. A study, co-authored by Pair Team researchers and peer-reviewed by theJournal of General Internal Medicine, evaluated Pair Team's community-integrated model, which blends medical, behavioral, and social care for Medicaid members with high rates of homelessness, serious mental illness, and chronic disease and it showed strong patient engagement and significant reductions in avoidable emergency and inpatient utilization. Batlivala says one in four hospital visits and one in two ER visits don't happen when a patient is in his company's care. But for years, delivering that level of care required human teams, which limited how fast and cheaply it could scale. Then, about nine months ago, Pair Team deployed a voice AI agent called Flora as its primary patient-facing interface. Flora is available 24 hours a day, handles intake, coordinates referrals, and does the check-ins that keep patients engaged between clinical visits. The first call that shifted his thinking was with a 67-year-old woman living out of her car, managing PTSD and congestive heart failure. She spoke with Flora for over an hour. "It was both incredible and depressing," Batlivala told me. "Flora was probably the only 'person' she'd talked to in weeks about her situation." Now, hour-long conversations with Flora are routine. "That's the companionship piece," he said. "And it turns out that is truly an intervention." The architects of ACCESS are themselves former startup operators. The program was designed by Abe Sutton, Director of the CMS Innovation Center, and Jacob Shiff, Chief AI and Technology Officer of the CMS Innovation Center. Sutton was previously a venture capitalist at a healthcare fund called Rubicon Founders. Shiff is a former healthcare founder. Both joined CMS under the Trump administration and their startup backgrounds are reflected in the program's design: outcome-based payments, direct-to-consumer enrollment, and a deliberate push for competition. There are real risks. Participants are feeding extraordinarily sensitive patient data — intimate conversations about housing and diseases and mental illness — into a federal infrastructure with a documented history of breaches, includingexposed Social Security numbers. For the vulnerable populations ACCESS is designed to serve, that's not an impractical concern. There are financial risks, too. The track record of CMS innovation programs is mixed. A 2023 Congressional Budget Officeanalysisfound that the CMS Innovation Center increased federal spending by $5.4 billion during its first decade rather than producing the projected savings. CMS is also paying less per patient per month than many participants anticipated, which means the math only works for organizations that have fully automated most of their patient interactions. Batlivala's answer to the reimbursement concern is that it's a feature, not a bug. "If you want to build a model that truly incentivizes the use of AI, the reimbursement rates have to be low," he told me. "The economics only work if you're running a lean, AI-first operation." Pair Team says it right now has partnerships in place that give it access to roughly 500,000 potential patients, and that it wants to reach a million within three years. Healthcare investors have been watching this closely. Digital health funding hit itshighest Q1 totalsince the pandemic this year, with AI companies capturing the bulk of it. But ACCESS has barely registered outside health tech trade press.

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Google adds Gemini-powered dictation to Gboard, which could be bad news for dictation startups

Google announced Rambler, a new AI-powered voice dictation feature for Gboard — its widely used Android keyboard app — at its Android Show: I/O Edition 2026 event on Tuesday morning. The launch puts Google in direct competition with the likes ofWispr Flow and Typeless, a growing crop of AI-powered dictation apps that have built audiences on desktop and mobile in recent years — most of which have yet to establish a strong foothold on Android. Just like other dictation apps, Rambler removes filler words like “ums” and “ahs.” It also understands midsentence corrections like, “I am going to meet you on Wednesday at our usual coffee shop at 3 p.m. … um, 2 p.m.” Google said it is using Gemini-based multilingual models that also support code switching. Code switching means users can move between languages midsentence — say, from English to Hindi — and Rambler will follow along without losing context. It’s a capability that reflects how many multilingual speakers actually communicate, and one that most Western dictation apps have been slow to support. The company said that Gboard will clearly indicate to its users that the Rambler feature is in use. It doesn’t store any voice recordings and uses the audio only to transcribe what users speak. Google mentioned during the briefing that, as you can use the Rambler feature across all apps, it is like “reinventing the keyboard.” Loading the player… On privacy, Ben Greenwood, director of Android Core Experiences, said Google uses a combination of on-device and cloud-based processing and has “invested significantly over many years” to ensure features are “safe and private” — a calculated message to users weighing Rambler against third-party dictation apps that may handle data differently. In the past few years, a host of dictation apps — Wispr Flow, Willow, Superwhisper, Monologue, Handy, and Typeless — have cropped up. But until now, most of that activity has been on desktop and iOS, leaving Android relatively underserved. Google itself releasedAI Edge Eloquent, an offline-first dictation app powered by its on-device Gemma AI models, on iOS last month. Rambler is Google's clearest move yet to close that gap. These new features will be limited to Samsung Galaxy and Google Pixel phones for an initial summer rollout but will eventually reach other Android devices. The core advantage here is distribution: Gboard is the default keyboard for the vast majority of Android users worldwide, meaning Rambler arrives pre-installed for hundreds of millions of people. When a platform player enters a market at the operating-system level, stand-alone apps need a compelling reason — better accuracy, deeper features, or stronger privacy guarantees — to justify a separate download. For dictation startups, the question is no longer whether they can build something good — it's whether they can build something good enough that users actively go looking for it.

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Report: Google and SpaceX in talks to put data centers into orbit

Google and SpaceX are in talks to launch orbital data centers in space,reportsThe Wall Street Journal, citing sources familiar with the matter. The potential deal comes as SpaceX gears up for its$1.75 trillion IPOlater this year, selling investors on the idea that data centers in space will be the cheapest place to put AI compute within the next few years. It also followsSpaceX’s deal with Anthropiclast week to use computing resources from xAI’s data center in Memphis, Tennessee, with the potential to work together on orbital ones in the future. (SpaceX acquired xAI in February.) Google is reportedly talking to other rocket-launch companies, as well. The company also plans to launch prototype satellites by 2027 as part of an initiative called Project Suncatcher, announced late last year. Elon Musk hascreated hypefor orbital data centers, claiming they are cheaper to operate. Advocates also point out they are free from local backlash that U.S. ground-based buildouts attract. However, asTechCrunch recently reported, today’s terrestrial data centers are much cheaper than those in orbit once satellite construction and launch costs are factored in. Google invested $900 million in SpaceX in 2015, according toregulatory filings. TechCrunch has reached out to Google and SpaceX for comment.

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Anthropic warns investors against secondary platforms offering access to its shares

As investors scramble to get their hands on shares of AI companies of all stripes, Anthropic this weekupdated its websiteto warn investors that a slew of private and secondary investment platforms that offer access to shares in the AI company are not, in fact, allowed to do so. The company named Open Doors Partners, Unicorns Exchange, Pachamama Capital, Lionheart Ventures, Hiive (new offerings), Forge Global (new offerings), Sydecar and Upmarket as companies that are not authorized to provide access to buy or sell its shares. “Any sale or transfer of Anthropic stock, or any interest in Anthropic stock, offered by these firms is void and will not be recognized on our books and records,” the company’ssupport pagereads. Reached for comment, Forge Global claimed to have been included erroneously. “We are working with Anthropic to remove Forge’s name from this alert,” the platform told TechCrunch. “Forge does not facilitate transactions in any private company’s shares without the explicit approval of the company.” Sydecar, meanwhile, said it only acts in an administrative capacity. “The company does not buy or sell securities or solicit transactions in any private companies. Further, Sydecar requires sponsors to attest that they have reviewed relevant documents relating to the transferability of shares and that they have the required approvals and consents from the company,” the company said in an emailed statement. Anthropic’s update comes alongside a rise in the number of investment platforms offering exposure to AI companies’ shares (and thus their growth) via secondary markets where existing shareholders sell their shares, “tokenized” securities, special purpose vehicles (SPVs), or secondary market holdings. Anthropic, rumored to beraising fresh funding at a $900 billion valuation, hasespecially been in demand, with some secondary market brokers telling TechCrunch last month that it’s one of the “hardest” stocks to source. "Anthropic is right to take seriously concerns around unauthorized share sales and investment scams," Hiive spokesperson Dakota Betts said in an emailed statement. "We share those concerns. They are a major reason why Hiive invested heavily in legal, compliance, and diligence infrastructure from the beginning, and all share transfers facilitated by Hiive are approved by the issuer." Over the past year, some crypto companies, likecrypto exchange OKX, have spun up investment products selling exposure to AI companies. These often take the form of pre-IPO perpetual futures contracts, which are derivative instruments that track the value of private companies on secondary markets but don't offer ownership of actual shares. SPVs are different from those derivative systems, offering investors a chance to buy shares of an entity that holds at least some stake in Anthropic. That equity could be from an official investor, or have been acquired when an investor is forced to liquidate its holdings, as happened duringthe bankruptcy of FTX. In other cases, the equity claim may be entirely fraudulent. Anthropic says both its preferred and common stock are subject to transfer restrictions, which means any share sale or transfer not approved by its board of directors will be considered invalid. According to Anthropic, any third-party platform (specifically SPVs and retail investment firms) that claims to sell its shares directly or using forward contracts are unauthorized to do so. "We do not permit special purpose vehicles (SPVs) to acquire Anthropic stock and any transfer of shares to an SPV are void under our transfer restrictions," the company's blog reads. "Offers to invest in Anthropic’s past or future financing rounds through an SPV are prohibited." Note: This story was updated to include comments from Hiive and Sydecar.

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