AI Infrastructure Expansion Drives Debt Surge and Market Volatility

Written byTianhao Xu
Tuesday, Nov 11, 2025 8:39 pm ET2min read
Aime RobotAime Summary

- AI infrastructure firms like

and are driving debt-fueled expansion, with capital expenditures outpacing financial capacity and net interest costs tripling.

-

projects AI/data center debt could dominate 20% of global investment-grade bonds by 2030, as companies like and scale operations through bond markets.

- Investor skepticism grows: CoreWeave trades at a 15x price-to-sales ratio despite losses, while

lost $150B in market value after Softbank's $5.8B stake liquidation.

- Systemic risks emerge as NVIDIA becomes de facto banker for AI infrastructure, creating a self-reinforcing cycle dependent on sustained investor appetite for high-risk debt.

The artificial intelligence (AI) infrastructure sector is undergoing a transformation marked by aggressive capital spending, ballooning debt loads, and volatile investor sentiment. (CRWV), a key player in this space, reported a 100% year-over-year revenue increase in its fiscal third quarter, accompanied by a narrower-than-expected adjusted loss of $0.22 per share. However, beneath these headline metrics lie structural risks. The company’s net interest expense has tripled to $311 million annually, and CFO Nitin Agrawal warned that 2026 capital expenditures will exceed $13 billion—far outpacing its current financial capacity. This pattern of debt-driven growth mirrors broader industry trends.

Nebius Group (NBIS), another AI infrastructure firm, explicitly outlined its reliance on debt financing during its third-quarter earnings call, with CFO Dado Alonso stating, “funding our growth will require raising a significant amount of capital.”

joins industry giants like Platforms (META) and (ORCL), which are similarly scaling AI operations through bond markets. JPMorgan analysts estimate that AI and data center issuers could constitute over 20% of the global investment-grade bond market by 2030, signaling a shift toward debt as a core funding mechanism for AI infrastructure.

The sector’s capital intensity is compounded by its dependence on hyperscalers such as Amazon, Microsoft, and Google, which control primary AI demand and outsource only incremental workloads. CoreWeave’s business model, for instance, is highly exposed to fluctuations in this spillover demand. If hyperscalers reduce their reliance on third-party providers, CoreWeave’s $1.5 billion backlog could lose relevance rapidly, leaving investors vulnerable to a leveraged infrastructure bet with limited downside protection.

Investor skepticism is evident in trading patterns. CoreWeave’s shares trade at a price-to-sales ratio of 15, a premium for a loss-making, debt-heavy business. Insider transactions further underscore this caution: 68 sell transactions by executives over six months, with no buybacks. Similarly, NVIDIA (NVDA) faced a selloff after Softbank, its largest shareholder, liquidated its $5.8 billion stake in October. The move triggered a 3% drop in NVIDIA’s stock price, erasing $150 billion in market value and reducing the company’s market cap from $5 trillion to $4.85 trillion. Seven NVIDIA executives and investors fell from the billionaire ranks in 13 days, with CEO Jensen Huang losing $11.2 billion in personal wealth.

The sector’s reliance on debt and equity markets raises systemic risks. NVIDIA, which has financed over $100 billion in compute-linked projects for partners like

and OpenAI, is positioning itself as the de facto banker for AI infrastructure. This creates a self-reinforcing cycle: chipmakers fund data centers that, in turn, purchase more chips. However, this ecosystem’s stability depends on sustained investor appetite for AI-related debt. If funding conditions tighten, as seen in CoreWeave’s abandoned $150 million acquisition of Core Scientific, growth trajectories could stall.

The macroeconomic implications are significant. AI infrastructure’s shift toward debt financing could amplify volatility in global bond markets, particularly if defaults rise in a sector with thin profit margins. For investors, the challenge lies in balancing AI’s transformative potential with its current financial fragility. As JPMorgan notes, the sector’s bond market dominance by 2030 hinges on maintaining investor confidence in its long-term viability.

author avatar
Tianhao Xu

Tianhao Xu is currently a financial content editor, focusing on fintech and market analysis. Previously, he worked as a full-time forex trader for several years, specializing in global currency trading and risk management. He holds a master’s degree in Financial Analysis.

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