Episode Details

Credit markets are stepping in to fund the surging demand for AI. Our experts Lindsay Tyler and Anish Shah explore the opportunities and risks behind this record financing wave.

Read more insights from Morgan Stanley.

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Lindsay Tyler: Welcome to Thoughts on the Market. I'm Lindsay Tyler, TMT Credit Research Analyst at Morgan Stanley. 

Anish Shah: And I'm Anish Shah, Global Head of Debt Capital Markets at Morgan Stanley. 

Lindsay Tyler: Today, how issuers and investors are approaching the rapidly evolving world of AI financing. 

It's Thursday, July 16th at 10am in New York. 

As AI demand accelerates, credit markets are being asked to finance infrastructure on a scale that used to be associated with utilities, telecom, or energy. That raises a central question for issuers and investors: How much debt can the AI ecosystem absorb? And at what price? 

Anish, can you walk our listeners through the key products in your purview? 

Anish Shah: Certainly, in my nearly twenty years at Morgan Stanley, this is probably the most incredible time period I've ever seen in the credit markets. I've had the privilege of working across a number of different roles in capital markets and lending. And a couple of years ago, we integrated the debt underwriting business across both investment-grade and leverage finance franchises in recognition of how interconnected the whole credit ecosystem has become. 

In addition to our core activities helping clients raise capital for their strategic priorities, two of the big focus areas that we've had have been finding ways to harness the power of the private credit universe and also delivering best-in-class capabilities in funding this incredible growth in AI spend. 

Lindsay Tyler: AI financing has certainly been a theme we've also been focused on in research. Our equity research colleagues project that a handful of key players could add more than 30 gigawatts of capacity over a two-year timeframe, driving around [$]2 trillion of aggregate cash CapEx in that period. And to put that into context, a single gigawatt of data center capacity can require roughly $12 billion for the shell, and then often more than double that for chips and racks. 

So, from your vantage point, what inning are we in? And what gives you confidence that credit markets can continue funding this opportunity at scale? 

Anish Shah: I mean, Lindsay, the numbers certainly are staggering, as you note. And if you just observe the CapEx estimates for the hyperscalers and broadly for AI infrastructure, we're certainly in the early innings. 

Lindsay Tyler: Mm-hmm. 

Anish Shah: The largest tech companies have historically, as you know, raised very little debt. In fact, many of these companies have not even needed a credit facility. As CapEx projections were materially increased in the second half of last year, we saw the beginning of scaled capital raises. Hyperscaler issuance has quickly gone from less than one percent of the investment-grade market to more than 10 percent of the market. 

You know, as I look ahead, based on what we're seeing on the ground, we think that AI-related funding, whether it's for data center development or financing compute capacity, could top 15 percent of the total issuance across all credit products. 

This has been an unprecedented test for the capital markets, both in terms of the depth of capacity and the breadth of product. The teams have been on the forefront of deep investor dialogue and product innovation. 

This spans corporate investment grade, first of their kind financings in high-yield and leveraged loan