It takes a lot of computing power to run an AI product — and as the tech industry scrambles to harness the power of AI models, there’s a parallel race underway to build the infrastructure to power them. In one recent earnings callNvidia 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. In the process, they put enormous strain on power grids and push the industry’s building capacity to its limits.
Below, we’ve laid out everything we know about the biggest AI infrastructure projects, including big spenders from Meta, Oracle, Microsoft, Google, and OpenAI. We’ll keep this updated as the boom continues and the numbers climb even higher.
Microsoft’s 2019 investment in OpenAI
This is arguably the deal that started the entire modern AI boom: In 2019Microsoft made a $1 billion investment in a buzzy nonprofit called OpenAI, best known for its association with Elon Musk. Most notably, the deal made Microsoft the exclusive cloud provider for OpenAI — and as the demands for model training grew stronger, more Microsoft investment began to come in the form of Azure cloud credit rather than cash.
It was a win-win for both sides: Microsoft was able to claim more Azure sales, and OpenAI got more money for its biggest single spend. In the years that followed, Microsoft would build its investment up to nearly $14 billion—a move that’s set to pay off big once OpenAI turns into a profitable company.
The collaboration between the two companies has intensified more recently. Last year, OpenAI announced that it would no longer use Microsoft’s cloud exclusively, giving the company the right of first refusal on future infrastructure requirements, but pursuing others if Azure could not meet their needs. Microsoft has also begun exploring other foundational models to power its products with AI, establishing even greater independence from the AI giant.
OpenAI’s deal with Microsoft has been so successful that it has become common practice for AI services to be tied to a specific cloud provider. Anthropic has received $8 billion in investment from Amazon, while making kernel-level modifications to the company’s hardware to make it better suited for AI training. Google Cloud has also signed on smaller AI companies like Lovable and Windsurf as “major computing partners,” though those deals didn’t involve any investment. And even OpenAI is back in the well, getting a $100 billion investment from Nvidia in Septemberenabling him to buy even more of the company’s GPUs.
The rise of Oracle
On June 30, 2025, Oracle disclosed in an SEC filing that it had signed a $30 billion deal for cloud services with an unnamed partner. That’s more than the company’s cloud revenue for the entire previous fiscal year. OpenAI was eventually revealed as a partner, securing Oracle a place next to Google as one of OpenAI’s hosting partners after Microsoft. As expected, the company’s stock rose.
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A few months later, it happened again. On Sept. 10, Oracle revealed a five-year, $300 billion deal for computing power that will begin in 2027. Oracle stock soared even higher, briefly making founder Larry Ellison the richest man in the world. The sheer scale of the deal is staggering: OpenAI doesn’t have $300 billion to spend, so the number assumes massive growth for both companies and more than a little faith.
But before a dollar is spent, the deal has already established Oracle as one of the leading providers of AI infrastructure — and a financial force to be reckoned with.
Nvidia’s investment spree
As AI labs try to build infrastructure, they mostly buy GPUs from one company: Nvidia. That trade made Nvidia flush with cash — and it invested that cash back into the industry in increasingly unconventional ways. In September 2025, Nvidia bought a 4% stake in rival Intel for $5 billion — but even more surprising were the deals with its own customers. A week after Intel’s deal was revealed, the company announced $100 billion investment in OpenAIpaid for with GPUs to be used in OpenAI’s ongoing data center projects. Nvidia has since announced a similar deal with Elon Musk’s xAI and launched OpenAI a separate GPU-for-stock setup with AMD.
If this seems circular, that’s because it is. Nvidia GPUs are valuable because they’re so rare — and by trading them directly into an ever-expanding data center system, Nvidia is making sure they stay that way. You could say the same thing about OpenAI’s private stock, which is even more valuable because it can’t be acquired through the public markets. For now, OpenAI and Nvidia are riding high, and no one seems too worried — but if the momentum starts to play out, this kind of arrangement will be much more scrutinized.
Building hyperscale data centers of tomorrow
For companies like Meta who already have significant legacy infrastructurethe story is more complicated — though just as accurate. Meta CEO Mark Zuckerberg said the company plans to spend $600 billion on infrastructure in the US until the end of 2028.
In the first half of 2025, the company spent $30 billion more than the previous year, largely driven by the company’s growing AI ambitions. Some of that spending goes to big-ticket cloud contracts like a recent one $10 billion deal with Google Cloudbut even more resources are being poured into two massive new data centers.
A new 2,250-acre site in Louisiana, dubbed Hyperionit is estimated to cost about $10 billion to build and deliver 5 gigawatts of computing power. Specifically, the site includes an agreement with a local nuclear plant to manage the increased energy load. A smaller site in Ohio, called Prometheus, is expected to come online in 2026, powered by natural gas.
This type of construction has real environmental costs. Elon Musk’s xAI has built its own hybrid data center and power plant in South Memphis, Tennessee. The plant quickly became one of the biggest emitters of smog-producing chemicals in the county, thanks to a series of natural gas turbines that Experts say they violate the Clean Air Act.
Stargate Moonlight
Just two days after his second inauguration last January, President Trump announced a joint venture between SoftBank, OpenAI and Oracle to spend $500 billion on building artificial intelligence infrastructure in the United States. Dubbed “Stargate” after the 1994 film, the project arrived with incredible hype, with Trump calling it “the largest artificial intelligence infrastructure project in history.” OpenAI’s Sam Altman seemed to agree, saying, “I think this is going to be the most important project of this era.”
Broadly speaking, the plan was for SoftBank to provide the funding, with Oracle handling the creation with input from OpenAI. It was all overseen by Trump, who promised to remove any regulatory hurdles that could slow construction. However, there were doubts from the start, including from Elon Musk, Altman’s business rival, who claimed the project lacked the funds available.
As the hype has died down, the project has lost some momentum. In AugustBloomberg reported that the partners failed to reach a consensus. However, the project has moved forward with its construction eight data centers in Abilene, Texas;with construction of the final building completed by the end of 2026.
The capex crunch
“Capital expenditure” is usually a fairly dry metric, referring to a company’s expenditure on physical assets. But as tech companies lined up to report their capital spending plans for 2026, the rush of data center spending made the numbers much more interesting — and much bigger.
Amazon was the capex leader, forecasting spending of $200 billion in 2026 (up from $131 billion in 2025), while Google was a close second with an estimate of between $175 billion and $185 billion (up from $91 billion in 2025). Meta estimated $115 billion to $135 billion (up from $71 billion last year), though that number is a bit misleading because many of the data center projects have they kept their books completely away. Overall, overscalers plan to spend nearly $700 billion in data center projects in 2026 alone.
It was enough money to scare off some investors. However, companies were mostly undeterred, explaining that AI infrastructure was vital to the future of their companies. It has created a strange dynamic. As you might expect, tech executives are more bullish on AI than their counterparts on Wall Street — and the more tech companies spend, the more nervous their bankers get. Add to huge amounts of debt Many companies are stepping up to fund these jobs, and you’re starting to hear CFOs across the valley gnashing their teeth.
That hasn’t yet put a cap on AI spending, but it soon will — unless, of course, hyperscalers show they can pay off those investments.
This article was first published on September 22.
