AI Spending Spree Drives Global Tech Debt Issuance To Record High

Global technology companies sold a record amount of bonds in 2025 as they borrowed heavily to fund artificial intelligence infrastructure such as data centers and chips.​

How much debt and who is borrowing?

• Tech firms issued about $428.3 billion of bonds in 2025 through early December, the highest on record for the sector.​

• U.S. tech companies accounted for the bulk of this, around $341.8 billion, with the rest coming from Europe and Asia.​

• A small group of large “hyperscalers” (Amazon, Alphabet/Google, Meta, Microsoft, Oracle) have been especially active, together issuing around $100–120 billion in 2025 U.S. bond markets alone.​

Why is AI driving this?

• Companies are racing to build AI capacity, including GPU-heavy data centers, networking gear, and power infrastructure, which require very large upfront capital expenditure.​

• Even cash-rich firms are choosing to fund part of this through debt because borrowing costs have eased and investor demand for high-grade tech bonds is strong.​

• Analysts describe this as a structural shift: rapid obsolescence of AI chips and architectures forces continuous reinvestment, nudging firms to rely more on bond markets than in the past.​

Risks and debt metrics

• Across more than 1,000 listed tech firms, the median debt‑to‑EBITDA ratio has risen compared with earlier years, indicating debt is growing faster than earnings, though still below levels usually seen as dangerous.​

• The median operating cash flow‑to‑total‑debt ratio fell to a multi‑year low in 2025 before a modest recovery, showing some erosion in debt‑servicing capacity.​

• Credit spreads and credit default swap (CDS) costs for names like Oracle and Microsoft have widened, reflecting investors demanding a higher premium to hold their debt.​

Broader market impact

• AI-related borrowing is a major contributor to near‑record global corporate bond issuance, with estimates that roughly 30% of 2025 corporate debt sales were tied to AI infrastructure.​

• In indices such as the Bloomberg U.S. Corporate Index, the weight of big‑tech AI debt has inched higher, and some asset managers see potential for bouts of “indigestion” when large AI bond waves hit the market.​

• Rising AI capex is expected to keep bond supply elevated into 2026 and beyond, with forecasts that AI-linked corporate bond funding could ultimately reach hundreds of billions to over a trillion dollars over several years.​

What this means for investors

• For bond investors, AI debt offers exposure to highly rated, profitable issuers but with gradually increasing leverage and spread volatility.​

• For equity investors, the key question is whether AI spending delivers sufficient revenue and profit growth to justify the additional balance‑sheet risk taken on to fund it.​

  If AI investments fail to generate adequate returns, the main risks are higher corporate defaults, credit market stress, equity drawdowns, and broader economic weakness as firms cut back spending and jobs.​

  Company-level risks

  • Debt stress and downgrades: Firms that financed AI with large bond issues could see leverage ratios spike relative to cash flow, leading to rating downgrades, higher refinancing costs, or, in extreme cases, default or restructuring.​

  • Overcapacity in data centers and chips would mean assets that are expensive to build but earn too little revenue, forcing impairment charges and margin compression.​

  • Management may respond with aggressive cost cutting, including layoffs and reduced R&D, which can damage long‑term competitiveness.​

  Risks to bond and credit markets

  • Credit spreads on tech and AI‑linked bonds could widen sharply if investors conclude that previous issuance was mis‑priced given the weaker earnings outlook.​

  • A large volume of AI‑related debt needing rollover in a more risk‑averse market could strain liquidity, making it harder or more expensive for companies to refinance.​​

  • Passive bond funds are particularly exposed because index weights rise as issuers sell more debt, potentially concentrating investors in credits whose fundamentals have deteriorated.​

  Equity and valuation risks

  • A shift in AI sentiment—away from “revolution” toward “overhype”—could trigger sharp falls in AI‑exposed tech stocks, similar to the dot‑com and telecom busts when infrastructure returns lagged expectations.​

  • Lower equity prices reduce firms’ ability to raise fresh capital, amplify wealth effects on households, and may cause risk‑off moves across growth and tech sectors more broadly.​

  • Venture and private equity portfolios heavily tilted to AI could suffer markdowns, hitting institutional investors such as pension funds and endowments.​

  Macroeconomic and financial‑stability risks

  • If AI capex proves excessive, companies are likely to cut investment, push fewer projects through, and slow hiring, which would drag on GDP growth, especially in the U.S. and other tech‑heavy economies.​

  • A broad AI‑related asset price correction (equities and credit) could tighten financial conditions, reduce lending, and increase the risk of a wider downturn.​

  • Concentration of AI risk in a small number of very large firms means shocks to their balance sheets and securities could propagate quickly through indices and portfolios worldwide.​

  What this means for investors

  • Portfolios concentrated in AI‑themed equities and credit face elevated downside if earnings fail to match the investment surge; diversification across sectors, regions, and asset classes becomes more important.​

  • Higher‑quality, longer‑duration government and investment‑grade bonds outside the most leveraged AI issuers are highlighted by several asset managers as potential buffers in an AI‑disappointment scenario.​