AI Debt Issuance to Hit $570B in 2026, Fueling the Infrastructure Arms Race

The AI boom is entering a new phase—one financed not by venture capital or retained earnings, but by an unprecedented wave of corporate debt. Morgan Stanley’s latest analysis reveals that the world’s largest technology companies will borrow more than $570 billion this year alone to fund the next generation of artificial intelligence infrastructure. For the AI industry, this means data centers, specialized processors, and the entire compute supply chain are about to scale at a pace never seen before, reshaping both the technology landscape and the global credit markets in the process.

Morgan Stanley’s latest credit market report projects that global debt issuance tied to artificial intelligence will exceed $570 billion in 2026, more than doubling the pace of recent years. This surge reflects a fundamental shift in how the biggest technology companies finance the capital-intensive buildout of AI infrastructure—data centers, specialized computing clusters, and advanced chip supply chains. The investment bank notes that as of May 31, 2026, AI-related debt issuance had already reached nearly $236 billion, four times the level recorded during the same period a year earlier, underscoring the accelerating pace of borrowing. The hyperscalers—Alphabet, Amazon, Microsoft, and Meta—are expected to spend a combined $700 billion on capital expenditures this year, a figure that far outstrips their historically robust operating cash flows, pushing them to tap credit markets more aggressively than ever before.

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Morgan Stanley’s latest analysis reveals that the world’s largest technology companies will borrow more than $570 billion this year alone to fund the next generation of artificial intelligence infrastructure.

The magnitude of this financing pivot cannot be overstated. For decades, Big Tech firms enjoyed immense free cash flow that funded organic growth and even stock buybacks without significant leverage. Now, the race to capture the next wave of AI value is forcing them to issue bonds at scale, broadening investor bases through non-USD issuance to meet global demand. Morgan Stanley highlights that these companies are diversifying their debt profiles, issuing in euros, yen, and other currencies to attract a wider pool of institutional capital. This strategy allows them to lock in relatively favorable terms while credit spreads remain supportive, though the sheer volume of expected supply is beginning to weigh on bond prices. As Morgan Stanley puts it, “Fundamental (economic) backdrop remains strong, but for now we think (bond) price action is being mostly driven by supply expectations.”

The implications extend well beyond the hyperscalers themselves. The report points to a parallel trend in the semiconductor sector, where companies are leveraging debt to build out fabrication capacity in response to AI-fueled demand. This creates a self-reinforcing cycle: AI infrastructure investment drives debt issuance, which finances chip production capacity, which in turn enables more AI compute. The total addressable market for AI-optimized hardware is expanding so rapidly that traditional equity financing and cash reserves are no longer sufficient. Morgan Stanley’s forecast that hyperscaler capital expenditure will surpass $1 trillion in 2027 suggests that the debt spigot will remain wide open for at least the next two years.