According to reports, OpenAI is in discussions with semiconductor giant NVIDIA about a 10 GW AI data center campus in Pike County, Ohio, that will include up to $250 billion in lease and construction financing. The guarantee would cover funding for the facility and not NVIDIA's AI chips.
SB Energy, a subsidiary of SoftBank, would help OpenAI build the facility in Ohio. The project could eventually cost more than $500 billion, including the AI chips used inside the data center, and is expected to deliver 800 megawatts of power by 2028.
OpenAI, which is valued by private investors at around $1 trillion, continues to operate with no profit; given this, the proposed arrangement has raised questions. According to reports, NVIDIA has already invested $30 billion in OpenAI and is also in talks to provide hundreds of billions of dollars' worth of AI chips for future infrastructure.
Critics argue that financing mechanisms of this scale blur the line between genuine customer demand and vendor-supported expansion. They warned that if infrastructure spending outpaces revenue growth from AI, then every company in the AI ecosystem may become more dependent on projects that rely on debt and credit.
Recently, Burry published a software-sector research report and made it freely available on June 21, outlining which companies he believes are best positioned for the AI era and which face greater disruption risks.
Burry pushed back against claims that software companies are ‘dead’, arguing that large language models (LLMs) cannot replace human creativity. “LLMs, no matter how advanced they get at being LLMs, will never beat that creative instinct of a talented human being,” he wrote.
Boston College Associate Dean Aleksandar Tomic added concerns about the financing model of industry, adding that "What is happening right now with OpenAI and others is that they need computing, but apparently they don't really have the revenue or the financial capability to engage in the capital expenditures necessary to support their activities."
He also said, “They're paying themselves NVIDIA's money to get NVIDIA chips.”
However, not everyone has the same opinion. Michael Monaghan, founder of Founder's ETF, defended the broader investment cycle, stating, "That's not necessarily circular financing. That's just an economy."
Also Read: OpenAI Breach: NVIDIA Unites 35 Tech Giants in AI Alliance
Despite these concerns, the reported agreement reflects the unprecedented scale of investment in global AI infrastructure. Leading tech giants like Microsoft, Amazon, Google, and Meta continue investing hundreds of billions of dollars to build AI data centers and computing power for next-generation foundation models.
AI software, infrastructure, and related services are expected to exceed $631 billion globally by 2028, making businesses compete for their long-term computing resources, according to IDC.
Regardless of whether NVIDIA's proposed backstop ever gets traction, it raises a larger issue in the AI industry: can AI infrastructure investments keep growing at the current pace, or are increasingly complex financing models just going to pose challenges for the industry?
According to reports, NVIDIA is discussing a financing backstop of up to $250 billion to help OpenAI secure lease and construction funding for a 10 GW AI data center campus in Ohio. The guarantee would not include the cost of NVIDIA's AI chips.
Critics believe the arrangement could create a form of circular financing, where AI companies rely on funding from infrastructure partners to purchase products from the same ecosystem. They argue this may inflate demand and increase financial risk if AI revenue growth slows.
Michael Burry has questioned the sustainability of increasingly complex AI financing structures. While remaining optimistic about software innovation, he has warned that excessive debt-backed investments could become a vulnerability if market conditions weaken.
The proposed campus could eventually cost more than $500 billion and is expected to deliver around 800 megawatts of power by 2028, with long-term plans to support up to 10 gigawatts of AI computing capacity, making it one of the world's largest AI infrastructure projects.
The rapid adoption of generative AI has significantly increased demand for advanced chips, cloud infrastructure, and computing power. According to IDC, global spending on AI software, infrastructure, and related services is expected to exceed $631 billion by 2028, prompting technology companies to invest aggressively in next-generation AI facilities.