The historically high issuance of corporate bonds driven by AI investments, particularly from Big Tech companies, is being met by a rapidly expanding pool of passive credit funds. This dynamic is leading to concerns among some investors who believe that the indiscriminate buying of these funds could distort risk metrics and leave the market vulnerable. Max Lukianchikov of Goldman Sachs notes that the four largest tech companies have already issued over $170 billion in corporate debt this year, surpassing their total for 2025 and more than quadrupling their pre-AI annual average. Despite this massive supply, credit spreads remain tight, and volatility is low, largely because investors are attracted to the almost 6% "all-in yield" available due to higher government bond yields.
While bond market indicators like the ICE BofA U.S. Corporate Index Option-Adjusted Spread show no current signs of distress, remaining essentially unchanged since the start of the year, individual market participants like Torsten Slok, Chief Economist at Apollo, argue that this borrowing is already crowding out demand for U.S. Treasurys and other fixed-income investments. However, others like Todd Czachor, global head of fixed income research at Columbia Threadneedle, disagree, pointing to strong appetite for corporate bonds, even non-AI related issuance. Brij Khurana, a fixed-income portfolio manager at Wellington Management, also doesn't believe AI borrowing is currently crowding out other parts of the credit market, suggesting its effects are more visible in the stock market, where the Invesco KBW Bank ETF ($5.3 billion) has outperformed the S&P 500, while the Roundhill Magnificent Seven ETF ($3.6 billion) is flat.
Fitch Ratings highlights several potential credit risks associated with AI, including opacity in private credit structures, growing competition for assets, and limited transparency in complex fund arrangements driven by the rapid growth of massive digital infrastructure. They are particularly concerned about execution risks and potential labor displacement from AI, which could weaken tax revenues in developed economies. Barclays analysts project that hyperscalers like Microsoft, Amazon, Alphabet, and Meta could issue over $200 billion in debt this year alone, with borrowing expected to increase further in 2027, as Goldman Sachs estimates these companies will spend approximately $5.3 trillion on AI infrastructure through 2030.
