Credit markets are quietly becoming the financial backbone of the artificial intelligence build-out, as estimates from Morgan Stanley and Moody’s Ratings suggest at least $3 trillion of capital spending will be needed for data centers and related infrastructure in the coming years, with JPMorgan JPM projecting more than $5 trillion once power generation is included. Even the largest technology companies, including Amazon, Microsoft and Meta Platforms, do not appear positioned to fund that scale of investment using internal cash alone, pushing borrowers toward a broad mix of debt markets. Bank of America estimates AI-related companies raised at least $200 billion through debt last year, likely an undercount given the volume of private deals, with issuance expected to climb into the hundreds of billions of dollars in 2026, a trend that could gradually influence borrowing costs across the wider corporate market.

This funding wave is unfolding as equity portfolios are already heavily tilted toward AI-linked stocks, with the Magnificent 7 which include Alphabet GOOG, Apple AAPL, Nvidia NVDA and Tesla TSLA accounting for about a third of the S&P 500’s value, making diversification increasingly difficult. JPMorgan credit strategists note that bond portfolios, which historically moved more closely with interest rates and bank performance, could now become more correlated with the operating fortunes of large technology companies as AI debt issuance expands. Morgan Stanley expects $250 billion to $300 billion of debt issuance in 2026 from hyperscalers and related joint ventures alone, while off-balance-sheet project finance structures backed by long-term leases are emerging as a key mechanism to fund massive data-center projects without overwhelming corporate balance sheets.

Still, the breadth and complexity of this lending boom is introducing risks that investors are beginning to scrutinize more closely. The Bank for International Settlements has warned that rising leverage among AI firms could amplify financial shocks if adoption or revenue growth materializes more slowly than expected, while rapid advances in technology raise the possibility that data centers and GPUs financed today could become obsolete before their debt is repaid. Exposure is spreading beyond investment-grade issuers into high-yield bonds, private credit, structured finance and GPU-backed loans tied to companies such as xAI and CoreWeave, making it harder to track aggregate risk. For investors, the opportunity to participate in the AI infrastructure build-out could be significant, but it may increasingly hinge on execution discipline, refinancing conditions and the pace at which AI demand ultimately develops.