A significant amount of computational capacity is necessary to operate an AI product — and while the tech sector quickly seeks to harness the capabilities of AI models, there is a simultaneous endeavor to construct the infrastructure that will support them. In a recent earnings call, Nvidia CEO Jensen Huang projected that by the decade’s end, investments in AI infrastructure will reach between $3 trillion and $4 trillion, primarily from AI enterprises. This endeavor is exerting tremendous pressure on power grids and pushing the industry’s construction capacity to its edge.

Below, we have compiled all known details regarding the largest AI infrastructure initiatives, including substantial investments from Meta, Oracle, Microsoft, Google, and OpenAI. We will continue to update this information as the boom persists and the figures rise further.

Microsoft’s 2019 investment in OpenAI

This is arguably the agreement that initiated the entire modern AI surge: In 2019, Microsoft invested $1 billion in an exciting non-profit known as OpenAI, primarily recognized for its connection with Elon Musk. Importantly, this arrangement designated Microsoft as OpenAI’s exclusive cloud service provider — and as the demands for model training intensified, a larger portion of Microsoft’s investment began to be delivered as Azure cloud credits instead of cash.

It proved beneficial for both parties: Microsoft was able to report increased Azure sales, while OpenAI received additional funding for its major expenditure. In the ensuing years, Microsoft would elevate its investment to nearly $14 billion — a strategic move likely to yield significant returns once OpenAI transitions to a profit-driven entity.

The relationship between the two firms has unraveled more recently. Last year, OpenAI declared it would no longer exclusively utilize Microsoft’s cloud, offering the company a right of first refusal for future infrastructure needs while exploring other options if Azure couldn’t accommodate them. Microsoft has also started pursuing alternative foundational models for its AI products, aiming for greater autonomy from the AI behemoth.

OpenAI’s success with Microsoft has prompted a trend among AI services to partner with specific cloud providers. Anthropic has secured $8 billion in funding from Amazon, modifying the hardware at the kernel level to better support AI training. Google Cloud has also partnered with smaller AI firms like Lovable and Windsurf as “primary computing partners,” although these agreements didn’t include direct investments. OpenAI has additionally returned for more support, garnering a $100 billion investment from Nvidia in September, enabling it to acquire a greater number of the company’s GPUs.

The rise of Oracle

On June 30, 2025, Oracle disclosed in an SEC filing that it had entered into a $30 billion cloud services agreement with an unnamed partner; this exceeds the company’s total cloud revenues for the preceding fiscal year. OpenAI was ultimately disclosed as the partner, positioning Oracle alongside Google as one of OpenAI’s series of hosting partners post-Microsoft. Unsurprisingly, the company’s stock surged.

A few months later, another significant announcement was made. On September 10, Oracle unveiled a five-year, $300 billion arrangement for computing power, set to commence in 2027. Oracle’s stock ascended even further, briefly positioning founder Larry Ellison as the wealthiest individual globally. The immense scale of this deal is astonishing: OpenAI does not possess $300 billion to allocate, suggesting significant growth expectations for both companies, coupled with a degree of optimism.

However, even before any funds are utilized, the arrangement has solidified Oracle’s place as a primary AI infrastructure provider — and a formidable financial entity.

Nvidia’s investment spree

As AI laboratories rush to create infrastructure, their primary source for GPUs has been one company: Nvidia. This trading has resulted in Nvidia accumulating substantial capital — which it has reinvested into the industry in progressively unconventional ways. In September 2025, Nvidia acquired a 4% stake in competitor Intel for $5 billion — yet even more surprising have been the agreements with its own clients. A week subsequent to the Intel transaction, Nvidia announced a $100 billion investment in OpenAI, compensated with GPUs that would be allocated to OpenAI’s ongoing data center initiatives. Nvidia has since revealed a comparable deal with Elon Musk’s xAI, while OpenAI initiated a separate GPU-for-equity arrangement with AMD.

If that seems circular, it’s because it is. Nvidia’s GPUs are coveted due to their scarcity — and by exchanging them directly into an ever-expanding data center initiative, Nvidia is ensuring they remain that way. The same can be said for OpenAI’s privately held stock, which becomes increasingly valuable as it is unavailable through public markets. Currently, both OpenAI and Nvidia are thriving and there’s little anxiety — but should the momentum begin to wane, this set-up will face significantly more examination.

Building tomorrow’s hyperscale data centers

For organizations like Meta, which already possess substantial legacy infrastructure, the situation is more intricate — though equally costly. Meta CEO Mark Zuckerberg has stated that the firm intends to invest $600 billion in U.S. infrastructure by the end of 2028.

In the first half of 2025, the company allocated $30 billion more than the previous year, primarily driven by its expanding AI goals. Part of that expenditure was directed towards high-value cloud contracts, such as a recent $10 billion agreement with Google Cloud, but even more resources are being funneled into two enormous new data centers.

A new 2,250-acre location in Louisiana, named Hyperion, is anticipated to incur an estimated $10 billion in construction costs and is expected to provide around 5 gigawatts of computing power. Significantly, the site includes a partnership with a local nuclear power facility to accommodate the augmented energy demand. A smaller facility in Ohio, referred to as Prometheus, is slated to become operational in 2026, fueled by natural gas. 

That type of expansion comes with tangible environmental repercussions. Elon Musk’s xAI constructed its own hybrid data center and energy-generation plant in South Memphis, Tennessee. The facility has swiftly become one of the county’s largest emitters of smog-generating chemicals, due to a series of natural gas turbines that experts assert violate the Clean Air Act.

The Stargate moonshot

Just two days following his second inauguration last January, President Trump announced a collaborative initiative involving SoftBank, OpenAI, and Oracle, aiming to invest $500 billion in the development of AI infrastructure within the United States. Dubbed “Stargate” after the 1994 film, the project arrived with immense anticipation, with Trump labeling it “the largest AI infrastructure endeavor in history.” OpenAI’s Sam Altman seemed to concur, stating, “I believe this will be the most significant project of this era.” 

In basic terms, the proposal involved SoftBank providing the financing, while Oracle managed the construction with guidance from OpenAI. Trump oversaw the entire operation, pledging to eliminate any regulatory obstacles that might delay the project’s progress. Yet, doubts surfaced from the onset, including from Elon Musk, Altman’s business adversary, who alleged the initiative lacked the necessary funding.

As the initial excitement has subsided, the project has experienced a decline in momentum. In August, Bloomberg reported that the collaborators were struggling to reach agreement. Nevertheless, the initiative has continued with the construction of eight data centers in Abilene, Texas, with the final building expected to be completed by the end of 2026.

The capex crunch

“Capital expenditures” usually refers to a company’s investment in physical assets, a rather dull metric. However, as tech companies prepared to announce their capex forecasts for 2026, the surge in data center spending transformed the figures into something much more engaging — and significantly larger.

Amazon led the pack in capex, projecting $200 billion in spending for 2026 (up from $131 billion in 2025), while Google closely followed with estimates ranging from $175 billion to $185 billion (up from $91 billion in 2025). Meta estimated expenditures of $115 billion to $135 billion (up from $71 billion the previous year), although this figure is somewhat misleading as many data center projects have been omitted from their financial reports. Overall, hyperscaler firms are planning to invest nearly $700 billion in data center initiatives in 2026 alone.

This influx of capital has caused some concern among investors. Most companies, however, remain unfazed, emphasizing that AI infrastructure is crucial for their future. This has created a peculiar dynamic. As expected, tech leaders are more optimistic about AI than their Wall Street counterparts — and the larger the investments tech companies make, the more apprehensive their bankers become. When added with the considerable debts many firms are incurring to finance these expansions, it’s not uncommon to hear CFOs throughout Silicon Valley grinding their teeth.

Although this has yet to slow AI expenditures, it may soon — unless, of course, hyperscalers can demonstrate that these investments yield substantial returns.

This article was initially published on September 22.