Is AI-related debt an issuer problem or a concern for broader credit markets?

Recent headlines around large AI-related bond deals from hyperscalers’ have raised understandable questions from investors. Is Big Tech suddenly loading up on debt to fund massive AI capex? And does that create new risks for broader credit markets and investors?

At the issuer level, we think the answer is no. The public and private companies at the center of the AI build-out have very strong balance sheets. As shown, debt to enterprise value¹ across this cohort sits comfortably below 5% with only one exception. In some cases, these firms hold more cash than debt, leaving them in a net cash position even after recent bond issuance, a sign of balance sheet strength.

So, if the initial investment phase was fueled by equity and cash, why issue debt at all? For management teams, this is not a sign of stress but an exercise in capital efficiency. Issuing debt allows companies to:

• Lock in long-dated funding that matches the multi-year nature of AI and data-center investment.
• Preserve cash on the balance sheet for flexibility, buybacks and other strategic opportunities.
• In most cases, the cost of investment-grade debt remains attractive relative to the cost of equity.

In summary, using the bond market to fund long-term AI capex is a rational decision, not a signal of financial strain.

The more important question, in our view, is what this wave of issuance means for broader credit markets. The size of these bond deals is massive. For context, Meta recently issued around $30 billion across a 6-part bond sale tied to data-center spending, while total new investment-grade supply month-to-date is ~$136bn². When one issuer accounts for almost 25% of supply, that concentration has implications for valuations and liquidity. Amazon and others have also announced or completed new bond deals, further adding to technology sector supply.

In the near term, such lumpy, sector-concentrated supply can pressure spreads wider as markets digest the new paper, particularly at longer maturities. Indeed, tech sectors spreads have widened from 69bps in mid-August to 88bps, currently. Moreover, the investment-grade universe has become more tech-heavy, increasing concentration risk for passive investors and sharpening the need for active security selection. Tech has risen from <2% of the IG credit market in 2005 to roughly 10% today.

For investors, the key takeaway is that the risk is not that AI leaders are suddenly over-levered. On most balance-sheet metrics, these companies remain very strong, and their use of debt can be seen as a disciplined financing choice. The more relevant question is how this new tech supply influence sector weights, benchmark composition and spread levels. We would argue periods where spreads temporarily widen presents opportunities to add high-quality issuers.

In short, the story is less about deteriorating credit quality in Big Tech and more about how investors position around a larger, more influential technology footprint in the investment-grade credit market.

¹ Net debt to enterprise value is a leverage ratio that measures total debt less cash relative to the sum of market cap, total debt, preferred equity, minority interest less cash and cash equivalents.

² Gross new supply and does not take into account refinancing. 

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