Three Bank for International Settlements (BIS) economists said Monday (March 16) that banks could be impacted by a trend in which artificial intelligence hyperscalers are tapping private credit firms to help build AI infrastructure.
Amid the rapid increase in investment in AI infrastructure, hyperscalers have turned to both corporate bond markets and off-balance sheet arrangements, which are often formed in partnership with private credit firms, BIS Senior Economist Egemen Eren, Visiting Economist Ingomar Krohn and Senior Economist Karamfil Todorov wrote in the BIS Quarterly Review published Monday.
The off-balance sheet arrangements are often structured as dedicated vehicles such as joint ventures or special purpose entities that acquire or develop data centers, allowing hyperscalers to keep most of the associated debt off their balance sheet, according to the article.
“These arrangements amount to ‘shadow borrowing’: obligations that are economically akin to debt but largely reside outside corporate balance sheets,” the authors wrote. “By channeling sizeable private credit into AI infrastructure, these structures strengthen links between hyperscalers and non-bank investors such as private credit vehicles and insurers. Banks support the vehicles with funding lines, potentially creating new shock transmission channels — eg via refinancing pressures at the vehicle level, procyclical shifts in private credit appetite or the activation of guarantees.”
It was reported in August 2025 that UBS Global Research advised investors looking at the AI industry to keep an eye on overheating risk and the health of the asset class.
UBS strategists said private credit lenders were becoming an important source of capital for the industry. They noted that private debt loaned to the technology sector had increased by $100 billion over the previous 12 months, reaching a total of $450 billion, while business development companies’ tech lending leapt from $80 billion to $150 billion.
“This phenomenon could sustain significant growth plans for AI and other hyperscaler companies, sowing the seeds of an upside scenario and increasing overheating risk,” the UBS strategists wrote.
PYMNTS reported in September 2025 that as companies sprint to build the data centers and buy the chips needed to train and run large language models, they are financing these efforts not just by venture dollars but by borrowing.
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