How Big Tech's AI Build-Out is Shifting Capital Allocation Toward Private Credit

The artificial intelligence (AI) revolution is reshaping not only technology but also the financial architecture underpinning its development. As Big Tech firms race to dominate the next frontier of innovation, their capital allocation strategies are increasingly diverging from traditional financing models. Instead of relying solely on public debt or equity markets, companies like Meta, Amazon, and Microsoft are turning to private credit-a structural shift that is redefining risk-return dynamics and unlocking new investment opportunities in the private capital ecosystem.

The Surge in AI Infrastructure Spending and Non-Traditional Financing

Big Tech's AI infrastructure spending has skyrocketed, with collective capital expenditures reaching $364 billion in 2025-a 12% increase from 2024. This surge is driven by the need to scale generative AI models and secure supply chains amid global export controls. However, the sheer magnitude of these investments has pushed companies to adopt complex, non-traditional financing methods. For instance, Blackstone's $3.46 billion CMBS offering to refinance QTS Data Centers-a major AI infrastructure player-highlights the growing reliance on securitization markets. Similarly, hyperscalers are leveraging asset-backed securities (ABS) to diversify their debt, with $13.3 billion in ABS backed by data centers issued across 27 transactions in 2025 alone. These strategies allow firms to manage balance sheet constraints while accessing liquidity at scale.

Private Credit's Expansive Role in AI Infrastructure

Private credit has emerged as a critical funding vehicle for AI infrastructure, filling gaps left by traditional banks and public markets. From 2023 to 2025, private credit assets under management (AUM) surged from $1.6 trillion to a projected $3 trillion by 2028, driven by institutional demand for higher-yielding assets and the withdrawal of banks from mid-market lending. This growth is particularly pronounced in AI-linked sectors, where private credit offers tailored solutions for capital-intensive projects. For example, Meta raised $60 billion through a hybrid of private placements and public bond issuances to fund its data center expansion, while Oracle secured a $38 billion high-grade loan for its Vantage data centers according to Reuters. These cases underscore private credit's flexibility in structuring long-term, customized financing for AI infrastructure.

Structural innovations in private credit are further enabling this shift. Golub Capital has pioneered GPU-based financing through special purpose vehicles (SPVs), allowing AI companies to access high-performance computing resources without upfront capital outlays. These SPVs securitize future lease receivables, creating a circular financing model that preserves balance sheet flexibility for borrowers while offering attractive returns for lenders.

Investment Opportunities and Systemic Risks

The AI-driven debt boom presents significant opportunities for private credit investors. Analysts project that AI-linked investment-grade bond issuance could reach $1.5 trillion by 2030, while global data center capital expenditures are expected to near $7 trillion by the same year. This demand is attracting institutional investors, with 45% of respondents in Coller Capital's 2025 Global Private Capital Barometer planning to increase private credit allocations.

However, the rapid expansion of AI-related financing also raises concerns about systemic risk. The concentration of debt in a narrow set of borrowers and sectors could amplify contagion risks if demand for AI infrastructure slows or technological obsolescence accelerates. For example, Morgan Stanley estimates that $800 billion in private credit will be required over the next two years to fund the global data center buildout, yet many of these loans are opaque and lack the regulatory safeguards of public markets. Additionally, the interconnection between AI financing and energy markets-via long-term power-purchase agreements and direct investments in generation infrastructure-introduces new channels of risk for energy companies.

Conclusion: A New Era of Capital Allocation

Big Tech's AI build-out is catalyzing a fundamental reallocation of capital toward private credit, driven by the need for flexibility, scalability, and innovation in financing. While this shift offers lucrative opportunities for investors, it also demands a nuanced understanding of the structural risks inherent in opaque, high-growth markets. As the AI infrastructure boom continues, the private credit sector's ability to balance innovation with prudence will be critical in shaping the next phase of the digital economy.