How Credit Markets Could Finance AI’s Trillion Dollar Gap

Until now, the AI buildout has largely been self-funded. Our Chief Fixed Income Strategist Vishy Tirupattur and our Head of U.S. Credit Strategy Vishwas Patkar explain the role of credit markets to fund a potential financing gap of $1.5 trillion as spending on data centers and hardware keeps ramping up.

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Vishy Tirupattur: Welcome to Thoughts on the Market. I am Vishy Tirupattur, Morgan Stanley's Chief Fixed Income Strategist.

Vishwas Patkar: And I'm Vishwas Patkar, Head of U.S. Credit Strategy at Morgan Stanley.

Vishy Tirupattur: Today we want to talk about the opportunities and challenges in the credit markets, in the context of AI and data center financing.

It's Wednesday, August 6th at 3pm in New York.

Vishy Tirupattur: So, Vishwas spending on AI and data centers is really not new. It's been going on for a while. How has this CapEx been financed so far predominantly? What has changed now? And why do we need greater involvement of credit markets of different stripes?

Vishwas Patkar: You're right, Vishy. So, CapEx on AI is certainly not new. So last year the hyperscalers alone spent more than $200 billion on AI related CapEx. What changes from here on, to your question, is the numbers just ramp up sharply. So, if you look at Morgan Stanley's estimates leveraging work done by our colleague Stephen Byrd over the next four years, there's about [$]2.9 trillion of CapEx that needs to be spent across hardware and data center bills.

So what changes is, while CapEx so far has been largely self-funded by hyperscalers, we think that will not be the case going forward. So, when we leverage the work that has been done by our equity research colleagues around how much the hyperscalers can spend, we've identified a [$]1.5 trillion financing gap that has to be met by external capital. And we think credit would play a big role in that.

Vishy Tirupattur: A financing gap of [$]1.5 trillion. Wow. That's a big number, by any measure. You talked about multiple credit channels that would need to be involved. Can you talk about rough sizing of these channels?

Vishwas Patkar: Yep. So, we looked at four broad channels in the report that went out a few weeks ago. So, that [$]1.5 trillion gap breaks out into roughly [$]800 billion across private credit, which we think will be led by asset-based finance. Another [$]200 billion we think will come from Investment Grade rated bond issuance from the large tech names. Another [$]150 billion comes through securitized credit issuance via data center ABS and CMBS. And then finally there is a [$]350 billion plug that we've used. It's a catchall term for all other forms of financing that can cover sovereign spend, PE (private equity), VC among others,

Vishy Tirupattur: The technology sector is fairly small within the context of corporate grade markets. You are estimating something like [$]200 billion of financing to come from this channel. Why not more?

Vishwas Patkar: So, I think it comes down to really willingness versus ability. And, you know, you raise a good point. Tech names certainly have a lot of capacity to issue debt. And when I look at some of the work done by my colleague Lindsay Tyler in this report, the big four hyperscalers alone could issue over [$]600 billion of incremental debt without hurting their credit ratings.

That said, our assumption is that early in the CapEx cycle, companies will be a little hesitant to do significantly debt funded investments as that might be seen as a suboptimal outcome for shareholder returns. And that's why we have reduced the magnitude of how much debt is