Credit Markets
The Capital Behind the Code
By: Brandon Chi
While stocks mainly grab the headlines, the credit markets are quietly underwriting the infrastructure behind artificial intelligence – from data centers to semiconducting, it forms record bond issuance and private lending. The equity rally defines the face of the AI boom, but its backbone is financed through debt. Lots of it.
Over the past year, AI-related capital expenditures have exploded, with hyperscale cloud providers, chipmakers, and utilities racing to expand their capacity. The ‘Fear of Missing Out’ is high amongst the competition within the AI race. To fund this, companies are leaning heavily on the bond and loan markets. Corporate bond issuance tied to technology and infrastructure is up double digits YoY, while private credit funds are deploying billions into long, structured deals that fall between the cracks in the media. It’s an arms race, and beneath every NVIDIA headline, lies a web of lenders building the capital of the AI era.
Wall Street’s Quiet Gold Rush
The AI boom isn’t only an equity story; it’s an infrastructure story. Behind every AI model, or hyperscale farm sits a web of debt financing. These are often stitched together by investment banks, and institutions. According to Bloomberg, global data-center capital expenditures could exceed $1.3 trillion by 2027, and markets are already feeling the pull.
Investment-grade issuance tied to technology and utilities has risen 25% YTD as firms finance the data-center expansion. This goes the same for convertible-bond issuance from semiconducting, and equipment manufacturers are picking up. Even with 10-year yields hovering around 4.139 percent, spreads on these A-rated corporate debt remains tight, showing that credit markets are on a rewarding scale over conservatism.
Private-Credit Boom Behind the Scenes
Blue Owl Capital (NYSE: OWL) most notably, recently was behind the ~$27 billion financing for the “Hyperion” data-center in Louisiana. Described as the largest “private-credit deal ever.” Meta owns just 20% of the joint venture. Blue Owl-managed funds own 80%. It was arranged by Morgan Stanley, by issuing $27 billion in A+ rated debt, anchored by PIMCO and BlackRock.
“Does it even matter if you keep counting after you get to $1 trillion of capital expenditure in the next couple of years?” and “This is an area with no market leader, and we plan to be the market leader” says Blue Owl co-founder Marc Lipschultz. This truly shows a clear sign that institutional capital is now deeply embedded in the AI supply chain and poses many risks.
Insurers and pension funds as well, are hungry for steady yield in a volatile rate environment, such as this one. As they pour capital into these private asset vehicles, the AI infrastructure resembles as the new ‘real estate,’ with long, contracted deals.
However, the risk is high. Private-credit funds don’t trade in public markets, and their valuations depend heavily on demand. If AI-related demand cools, these loans could prove far less liquid than their ratings.
The AI credit boom shows a lot of different risks, with overleverage, liquidity, all the way to structural risks with the Magnificent Seven driving the way of computing demand. Yet the boom carries a quieter risk, the endless demand as of now. AI infrastructure requires enormous, fixed investment and long payback periods. These structures may insulate banks from direct exposure, but they push risk into other areas of the market. With banks being largely arrangers, and not lenders, who holds the real exposure? Credit funds, insurers, pensions, endowments, and asset managers are anchoring these multi-billion-dollar deals such as Hyperion. The investors earn a premium for illiquidity, until that liquidity disappears.
As of now, investor appetite remains avid, but history suggests that when every deal looks safe, credit quality may already be peaking. This isn’t the first time the financial system has funded a technological or industrial arms race through credit. The late-1990s telecom boom saw companies borrow heavily to lay fiber-optic networks that were supposed to carry an internet usage explosion that arrived years later. Similarly, the shale energy revolution of the 2010s was financed through high-yield bonds, that produced massive growth but waves of defaulting when commodity prices fell. The pattern is consistent; periods of transformative innovation attract capital and demand, and credit risk migrates towards investors.
Looking Ahead at the Cost of Intelligence
The next phase of the AI boom won’t be defined by breakthroughs in architecture or chip design, but really how the world finances them. Every new data center, GPU deal, or acquisition represents a long-term bet that AI’s value will justify today’s capital intensity. But these cycles test conviction. As yields fluctuate and investor appetite evolves, the cost of funding will determine who scales and who stalls. The internet was built on cheap capital, and the opposite will test artificial intelligence.
I believe that the challenge is sustainability. With a volatile rate market, every 100-basis point will increase funding costs, erasing billions in capital, and can increase internal rate of returns for founders. Still, the markets remain unfazed. As long as spreads stay tight and liquidity is there, Wall Street will keep financing the AI buildout with the same confidence that powered other groundbreaking innovations. AI runs on capital, and for now, capital still runs on credit.
