Yes. Credit investors should be concerned about rising artificial intelligence (AI)-related debt issuance for several reasons. Credit spreads are near historic lows and are likely to face pressure from surging bond supply, of which AI-related investment is just one driver. Fundamentals look healthy for most so-called “hyperscalers,” but other companies may see a concerning rise in leverage. Meanwhile, complex transaction structures in certain deals warrant scrutiny, particularly where obsolescence risk is a concern. Overall, as detailed in our 2026 Outlook, we believe the risk/reward trade-off for several credit markets remains unattractive.
Tight credit spreads are attracting issuers but offer little protection to investors if AI optimism fades or geopolitical risks, such as recent events in Iran, trigger a “risk-off” environment. US high-yield bond spreads of 289 basis points (bps) sit in the bottom decile of observed values. Similarly, although US investment-grade corporate spreads have risen slightly since reaching post-GFC lows in January, they remain in the lowest quartile on record. Spreads in adjacent markets also reflect stretched valuations: for example, commercial mortgage-backed security (CMBS) spreads have dramatically tightened over the last two years despite rising delinquencies.
Accelerating AI-driven capex could boost supply and put pressure on spreads. According to Morgan Stanley, gross US investment-grade supply will rise approximately 25% to a record $2.25 trillion in 2026, driven in part by hyperscaler and related infrastructure issuance rising to $400 billion—roughly 10x what they raised in 2024. Structured credit markets will also see surging supply, with data center securitizations expected to rise nearly 50% to more than $30 billion. Issuance is already well underway; Alphabet and Oracle together issued nearly $60 billion of new debt in February alone.
The financing of this AI-driven buildout will span the capital structure. Senior unsecured bonds will be the primary vehicle for large, investment-grade issuers. However, asset-backed securities (ABS) and project finance debt are increasingly being used, especially for data centers. The ABS market is seeing innovation as data center cash flows are securitized to tap new pools of capital. As financing structures evolve, investors need to ensure they have a clear picture of leverage and risk. In some data center deals, for example, tenants effectively backstop the project, yet the transaction nonetheless sits off balance sheet, obscuring its risk profile.
The potential mismatch between the useful life of AI-related assets and the maturity of the debt used to finance them also warrants close attention. While demand for data center computing resources is currently robust—for example, waitlists for AI chips and capacity are common—future data center demand is uncertain. If AI models become more efficient or if a technological leap reduces the need for processing power, chips and the buildings that house them could become obsolete before their debt is repaid. This would threaten a variety of different debt instruments, including asset-backed deals that finance chip purchases, securitizations backed by data center revenue, and unsecured debt. The fiber optic buildout of the early 2000s offers a cautionary parallel: overbuilding led to years of excess capacity and financial distress for some issuers, though the long-term utility of fiber ultimately proved out.
Strong fundamentals help offset some of these risks. Many hyperscalers have high (AA or AAA) credit ratings, reflecting low leverage, strong free cash flow, and ample liquidity, making them well-positioned to absorb additional debt. However, not all players in the AI ecosystem generate such healthy operating cash flows, and even those that do will see capex demanding a growing share of this over the next several years. Utilities and REITs that own and operate data centers are taking on significant leverage to fund expansion but often start with different fundamentals. Utilities, for example, often carry BBB ratings, and some data center operators have “junk ratings,” a sticking point in recent financing deals.
Historically low credit spreads, in our view, do not sufficiently compensate investors for current risks, which include obsolescence and rising structural complexity. Given these challenges, credit exposure should remain within policy targets, and higher-quality structured credit, such as agency-backed mortgage securities, should be considered as a substitute for corporate bonds that offer only marginally higher yields but greater vulnerability to cyclical and technological risks. Investors in AI-related credits should focus on high-quality issuers with strong balance sheets and stable revenue streams. Complexity should be accepted only when compensated by a meaningful premium.
Wade O’Brien, Managing Director, Capital Markets Research