Over the last few months, artificial intelligence (AI)-related debt issuance from so-called hyperscalers (Amazon, Google, Meta, Microsoft, and Oracle) has flooded the investment-grade bond market. Historically, these firms have been largely absent from debt markets, relying instead on cash-heavy funding models for their near-term growth ambitions. As the AI race heats up, so does the debt issuance for its required development and infrastructure build. Year-to-date AI issuance has risen to over $100 billion, triple the past 10 years’ average of $32 billion annually and roughly 7% of the entire investment-grade market’s issuance thus far in 2025.
 

Predictions for future AI capital-expenditure (capex) spending vary, with J.P. Morgan forecasting $5 trillion in future capex, including $1.5 trillion funded from the investment-grade corporate bond market. Morgan Stanley puts the figure closer to $3 trillion in total capex, funded from a variety of sources, including the investment-grade corporate bond market. While estimates vary, the corporate debt issuance to fund AI capex will likely wind up in the hundreds of billions, if not trillions, of dollars.

This presents a challenge, particularly for passive bond investors. In traditional investment-grade benchmarks, a company’s weight increases as it issues more investment-grade debt, not because it is a better investment. This dynamic is often referred to as “the bums problem.” Active fixed-income managers carefully evaluate a company’s growing debt load, weighing the risk and return potential of each position. In contrast, passive bond funds and ETFs typically purchase these bonds to minimize tracking error, even if doing so means taking on additional credit risk. Could there be a stronger case for active fixed-income strategies?

Elevated AI debt issuance from the big tech names mentioned earlier has increased their weight in the Bloomberg U.S. Corporate Index only marginally over the past 12 months. The five companies’ current weight is 3.52%, up just 0.81% from a year prior. Nevertheless, if predictions for AI debt issuance play out, hyperscalers will likely play a larger role in investment-grade corporate bond benchmarks going forward.

As depicted in the table above, current net debt levels among most hyperscalers are low (with a few exceptions), supporting Standard & Poor’s (S&P) high credit ratings for most of the major players. However, big tech’s recent new issuance has generally come with concessions (i.e., wider spreads than issues with identical credit ratings). Several of our investment-grade managers have responded by selectively adding positions in this big tech, AI-related debt. In some cases, managers participated in the new issues and then sold them “on the break”—strategically buying the bonds at issuance and quickly exiting for a near-term profit.

Not all hyperscalers are created equal, and while most currently have healthy balance sheets, the market has grown wary of firms like Oracle that have issued a significant amount of debt on the hope of future revenue growth (as evidenced by rising spreads for the firm’s credit default swaps, seen as a gauge for a higher likelihood that its bonds will default).

Fortunately for fixed-income investors, you are not alone in navigating the ever-changing investment landscape; selecting skillful credit managers is a feature of SEI’s multi-manager research process. We conduct deep underwriting on each manager, including evaluating their ability to prudently underwrite credit fundamentals and assess relative value in a fast-moving market.

As with all new investment opportunities, the importance of detailed analysis and a healthy level of skepticism is warranted. As big tech’s scramble to raise, spend, and grow in the AI space continues, this will create opportunities and only serve to amplify the importance of active management.
















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