AI buildout needs $2 trillion debt as Wall Street may cover half

The AI infrastructure buildout could require more than $2 trillion in debt financing, yet Wall Street's investment-grade bond market may absorb less than half of that amount through 2030, according to Apollo's chief economist.

Torsten Slok, Apollo's chief economist, said Friday that AI-related borrowing accounts for more than 40 percent of new long-term, investment-grade corporate debt. "The AI ecosystem could support more than $2 trillion in debt," Slok said in a research note.

Investment-grade markets may absorb less than $1 trillion of that amount through 2030 because of "concentration and ratings constraints," Slok said. Investors already hold significant exposure to companies driving the AI buildout, and firms can only take on so much additional debt before ratings agencies view them as riskier borrowers. The gap, totaling more than $1 trillion, could be filled by private lenders and other financing backed by infrastructure, equipment and individual AI projects.

The financing shortfall comes as the largest technology companies project record capital spending. Amazon leads the Magnificent Seven with $220 billion in projected CapEx this fiscal year, ahead of Alphabet at $205 billion and Microsoft at $175 billion. Amazon, Alphabet, Microsoft and Meta combine for $738 billion in projected spending.

Private Credit Steps Into the Gap

Private financing deals could offer lenders better protection by tying debt to specific assets or contractual guarantees, Slok said, unlike traditional unsecured corporate bonds. Private lenders face fewer restrictions than public bond markets and can structure loans backed by data center assets or their future revenue streams.

The shift toward private credit has been building as mega-cap tech firms and data center operators raise billions of dollars to back new projects. Traditional bond markets have structural limits on how much debt they can absorb, largely because investors can only take on so much exposure to the same companies or industry. Apollo's analysis suggests the private credit market will need to scale significantly to close the gap, with asset-backed lending tied to specific infrastructure projects emerging as the preferred structure.

This dynamic mirrors the broader evolution of infrastructure finance, where private capital has increasingly filled voids left by public markets. For data center operators, the ability to secure project-level financing tied to contracted revenue from hyperscalers could prove more attractive than issuing unsecured corporate bonds that dilute existing creditors' claims.

Mega-Projects Push the Limits

The scale of planned AI infrastructure is unprecedented. Nvidia and OpenAI have reportedly discussed a data center near Columbus, Ohio, that could cost more than $500 billion, with OpenAI discussing a chip purchase valued up to $350 billion. The proposed 10-gigawatt site would dwarf the power output of other planned projects, including a $20 billion, 3.2-gigawatt center in Effingham County, Georgia, announced by OpenAI in July.

For investors, the financing gap carries systemic implications. If Wall Street cannot cover half of the $2 trillion funding need, companies may face higher borrowing costs, potential equity dilution, or slower AI infrastructure deployment. Given the concentration of these mega-cap tech names in the S&P 500, any strain on their balance sheets would ripple through the broader equity market. Nvidia shares have already shown sensitivity to AI financing concerns, losing $130 billion in market value in August as the firm reportedly entered a $500 billion AI financing deal.

The question now is whether private credit markets can scale fast enough to absorb the shortfall. Apollo's analysis suggests they can, but the transition from public to private financing will reshape how AI infrastructure gets funded — and who bears the risk.

This article is for informational purposes only and does not constitute investment advice.