In the past year, the world of artificial intelligence (AI) infrastructure has undergone a remarkable transformation, with surging investments, strategic pivots, and eye-popping financial deals capturing the attention of Wall Street and Silicon Valley alike. From the rise of private credit fueling data center expansion to legacy energy companies reimagining themselves as digital infrastructure powerhouses, the sector is experiencing a gold rush that few could have predicted just a few years ago.
According to Investorideas.com, global spending on AI infrastructure is projected to surpass $200 billion by 2028, a figure that underscores the magnitude of the current boom. In the first half of 2024 alone, organizations worldwide ramped up spending on compute and storage hardware for AI deployments by a staggering 97% year-over-year, reaching $47.4 billion. This surge isn’t just a blip—it’s a structural shift in how capital is being allocated and how the future of technology is being built.
One of the most striking developments has been the embrace of private credit as a primary engine for financing the physical backbone of AI. As reported by AInvest, traditional public debt markets have struggled to meet the unique needs of AI infrastructure projects, which often require long-term, patient capital and flexible deal structures. Private credit has stepped into this gap, offering tailored solutions such as unitranche loans, mezzanine financing, and performance-based interest structures that align with the capital-intensive and high-risk profile of AI ventures.
The numbers are nothing short of jaw-dropping. In 2025, Meta executed a $29 billion hybrid debt-equity financing deal with PIMCO and Blue Owl, structured as $26 billion in debt and $3 billion in equity. The debt component was priced at SOFR plus 375–425 basis points, with a 7–10 year tenor, reflecting the long-term nature of these investments. This deal allowed Meta to scale its AI operations—planning to deploy 1.3 million AI processors by 2026—without diluting shareholder equity or overburdening its balance sheet. The model has since been replicated by other giants: Microsoft entered a $30 billion partnership with BlackRock, and xAI Corp. raised $5 billion in syndicated debt, all in 2025.
Why has private credit become so attractive for these deals? According to AInvest, the answer lies in the yield premium and the stability of cash flows. Data center asset-backed securities (ABS) and commercial mortgage-backed securities (CMBS) now offer a 100–150 basis point premium over corporate bonds issued by hyperscalers, thanks to triple-net-lease structures and a steady stream of tenant revenue. For institutional investors, this is a rare opportunity to capture high-yield, asset-backed returns in an environment where traditional interest rates remain stubbornly low.
But it’s not just about the money. The physical infrastructure needed to power AI—massive data centers, robust power grids, advanced cooling systems, and proximity to renewable energy sources—has become a battleground for innovation and investment. U.S. data center financing is projected to reach $60 billion in 2025, with private credit firms like Apollo, KKR, and Brookfield leading the charge. Google’s $25 billion data center investment with Brookfield and Meta’s “hundreds of billions” in AI infrastructure plans highlight the scale and urgency of the buildout.
Blue Owl’s Digital Infrastructure Fund III, now fully capitalized at $7 billion, targets precisely these kinds of projects, focusing on AI and cloud infrastructure. As global demand for computing power is projected to reach $6.7 trillion by 2030, the need for new data centers and supporting energy infrastructure will only intensify. For investors who can secure early-stage deals, the window of opportunity is wide open—but it won’t last forever.
In the midst of this frenzy, new players are emerging and established companies are reinventing themselves. New Era Energy & Digital, Inc. (NASDAQ: NUAI), formerly New Era Helium, Inc., recently announced a strategic transformation, rebranding itself to reflect a new focus on vertically integrated energy supply and digital infrastructure. As reported by Investorideas.com, the company’s Texas Critical Data Centers (TCDC) project in Ector County is designed to deliver up to 1 gigawatt of AI and high-performance computing capacity, powered by clean energy. CEO E. Will Gray II put it plainly: “This name change marks the next chapter. It's a clear signal of who we are and where we're headed. We are the bridge between Silicon Valley and Houston, connecting the compute demands of tomorrow with the energy systems of today, for a shared digital future.”
This pivot isn’t just cosmetic. New Era is leveraging its expertise and assets in natural gas and helium—both crucial for semiconductor manufacturing—to build a platform that can serve hyperscale, enterprise, and edge operators. The company’s integrated approach, combining powered land, powered shells, and turnkey solutions, is designed to help clients accelerate data center deployment, optimize costs, and future-proof their investments.
The market has responded with enthusiasm to such moves. Vertiv Holdings Co., a key supplier of data center infrastructure, has delivered standout stock performance in 2025, rising 23% and far outpacing the S&P 500 Index’s 8.7% gain. Over the past twelve months, Vertiv stock surged nearly 97%, with much of the growth occurring after April. William Blair analysts recently rated Vertiv “Outperform,” citing its pivotal role in meeting the surging demand for AI-driven data center infrastructure. The company’s second quarter performance in 2025 was robust, with net sales hitting $2.64 billion, a 35% increase from the prior year, and a growing backlog of $8.5 billion.
Applied Digital Corporation, another major player, reported fiscal fourth quarter 2025 revenues of $38 million—up 41% from the prior year—and announced new data center leases with CoreWeave in North Dakota. These leases, spanning approximately 15 years, are expected to generate $11 billion in contracted revenue, a testament to the long-term nature and scale of current AI infrastructure projects. Wes Cummins, Chairman and CEO of Applied Digital, explained, “Over the past two years, we've streamlined our processes, enhanced our building design for greater flexibility, and established a repeatable approach supported by a strong supply chain. As a result, we've reduced projected build times from 24 months to 12 to 14 months, which we believe will enable us to deliver large-scale projects faster and more efficiently.”
CoreWeave, for its part, recently closed a $2.6 billion delayed draw term loan facility to support the purchase and maintenance of advanced equipment for its AI cloud platform, under a long-term agreement with OpenAI. Sarah Friar, CFO of OpenAI, highlighted the importance of such partnerships: “Scaling advanced AI requires world-class compute infrastructure, and partnering with CoreWeave and leading financial institutions enables us to train more capable models and deliver better experiences to people around the world.”
Despite the bullish outlook, some caution is warranted. Overcapacity in AI infrastructure could emerge by 2027, driven by aggressive expansion from hyperscalers. Energy cost volatility, particularly in regions reliant on fossil fuels, also poses risks. As AInvest notes, “Investors must prioritize lenders with strong underwriting discipline and diversification across geographies and technologies.”
Still, the overall sentiment remains optimistic. The AI infrastructure boom is not a fleeting trend, but a fundamental reordering of how capital, technology, and energy intersect. As the lines between public and private markets blur, and as more companies follow the lead of innovators like Willdan Group, Inc.—whose stock soared from $65.80 to $114.90 in less than two months—the rewards for those with foresight and discipline could be transformative.
With global computing power needs set to skyrocket and institutional appetite for high-yield, asset-backed returns on the rise, the next decade of AI infrastructure promises to be as dynamic as it is lucrative. Those watching closely—and acting boldly—are likely to shape the digital landscape for years to come.
