AI's Aggressive "Leverage Buildup"

Deep News
Nov 07

The grand narrative of the AI revolution is being built atop a growing mountain of debt. To meet the staggering computing demands of artificial intelligence, the data center construction boom is being fueled by unprecedented debt financing, with increasingly complex structures raising concerns among investors and regulators about potential bubble risks.

Recent data reveals that in September and October alone, AI-focused tech giants issued $75 billion in investment-grade bonds in the U.S. market—more than double the sector's annual average of $32 billion from 2015 to 2024. The financing frenzy has now expanded beyond traditional investment-grade bonds into riskier high-yield debt, less transparent private credit, and structured financial products that played controversial roles during the financial crisis. Observers including the Bank of England have warned about accumulating risks in opaque, illiquid corners of the financial system.

While proponents argue this differs from the late-1990s dot-com bubble—with cash-rich, profitable companies driving adoption—warning signs are emerging. From the divergence between Oracle's stock price and its credit default swaps (CDS) to Meta's off-balance-sheet financing for data centers, markets are scrutinizing the leverage behind AI's expansion.

**Tech Giants Lead Debt Surge Amid Mixed Signals** Tech titans are flooding debt markets to fund the AI race. Bank of America data shows $75 billion in AI-related U.S. investment-grade bond issuance in September-October, led by Meta's $30 billion and Oracle's $18 billion. Alphabet recently announced new borrowing plans, while Oracle's Vantage data centers secured a $38 billion senior loan. Though this represents just 5% of 2025's $1.5 trillion investment-grade bond volume, Barclays notes AI-related debt is now pivotal for forecasting 2026 credit supply. Complex structures are proliferating, such as Meta's $27 billion off-balance-sheet deal with Blue Owl Capital. JPMorgan estimates AI-linked firms now comprise 14% of its investment-grade index—surpassing U.S. banks.

Oracle's stock surged 54% in 2025 on AI-driven revenue hopes, potentially marking its best year since 1999. Yet its CDS costs have risen concurrently, signaling bond investors' unease about mounting debt—a divergence highlighting market anxiety over AI's leverage buildup.

**Financing Expands to Junk Bonds and Private Credit** AI's capital needs are reaching riskier territories. High-yield markets saw TeraWulf (a converted bitcoin miner) issue $3.2 billion in BB- rated bonds, while Nvidia-backed CoreWeave sold $2 billion in May. Private credit is also booming: UBS estimates AI-related private loans nearly doubled in the 12 months to early 2025. Though flexible, these opaque instruments could amplify systemic stress during downturns. Morgan Stanley predicts private credit may fund over half of global data center construction by 2028—an $800 billion opportunity.

**Structured Products Make a Comeback** Morgan Stanley suggests asset-backed securities (ABS) could fuel AI growth by securitizing future cash flows like data center leases. While digital infrastructure ABS ($80 billion) currently represents 5% of the $1.6 trillion U.S. ABS market, Bank of America notes an eightfold expansion in five years—with data centers backing 64% of deals. The segment may reach $115 billion by 2026. Though ABS are standard tools, their 2008 crisis legacy (when underlying assets collapsed) invites caution as they're repurposed for the tech revolution.

Disclaimer: Investing carries risk. This is not financial advice. The above content should not be regarded as an offer, recommendation, or solicitation on acquiring or disposing of any financial products, any associated discussions, comments, or posts by author or other users should not be considered as such either. It is solely for general information purpose only, which does not consider your own investment objectives, financial situations or needs. TTM assumes no responsibility or warranty for the accuracy and completeness of the information, investors should do their own research and may seek professional advice before investing.

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