AI Borrowing Creates a New Credit Playbook

3 Jun 2026 · 5 min · 1 chapter

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In short

How credit markets are evolving to finance the AI-driven CAPEX and data-center build-out, and what new constraints (power, labor, permitting, politics) may shape the pace.

Guests

No external guests mentioned; host is Vishy Tirupattur, Mogas Tarlay’s Chief Fixed Income Strategist.

Key claims

Hyperscaler CAPEX expectations have been revised sharply upward (from ~$450B in 2026/2027 to ~$800B in 2026 and ~$1.2T in 2027). Compute demand surged (OpenRouter weekly tokens up ~350% from ~6T to ~28T since early January). Credit financing has expanded across public/private markets, currencies, and issuer types, with structural innovation blurring boundaries between corporate and project finance.

Notable examples

Over $200B of public AI-related issuance in first five months; hyperscaler issuance exceeding large telecoms; GPU financing moving into broadly syndicated loans and asset-based financing/ABS; deal structures combining project finance elements, tranching, residual value guarantees, and hyperscaler-guaranteed leases.

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The Evolving Landscape of AI Financing

0:21 to 4:28

An analysis of the credit market's adaptation to AI-driven CapEx needs.

“When we first discussed the role of credit markets in financing the AI and the data center build-out around the middle of last year, the direction of travel was clear.”
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Transcript

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0:00Vishy Tirupattur:Welcome to Thoughts on the Market. I'm Vishy Tirupattur, Mogas Tarlay's Chief Fixed Income Strategist. Today, the critical question behind the AI-driven CAPEX cycle that is front and center for markets year-to-date. How is the credit market financing of this ecosystem evolving? It's Wednesday, June 3rd at 2 p.m. in New York. When we first discussed the role of credit markets in financing the AI and the data center build-out around the middle of last year, the direction of travel was clear. Realizing the transformative potential of AI requires unprecedented levels of CapEx. What has really surprised us since is the scale and speed of that spending, both of which have exceeded our expectations by a wide margin.

0:43Vishy Tirupattur:The upward revision in CapEx expectation has been dramatic. A year ago, we projected the combined CapEx of the five large hyperscalers at roughly$450 billion in both 2026 and 2027. After the first quarter earnings reports, Morgan Stanley Internet Equity Analyst, led by Brian Novak, now expect hyperscaler capex of roughly$800 billion in 2026 and$1.2 trillion in 2027. One data point really captures the surge in the underlying demand for compute. According to OpenRouter, the global weekly token usage, which is a key proxy for compute, has risen by roughly 350 % since early January, increasing from about 6 trillion tokens to 28 trillion tokens.

1:32Vishy Tirupattur:Credit channels for financing this CapEx have not only been broader and deeper than we anticipated, spanning public and private markets, but have been remarkable in the structural innovation that is blurring the lines between public and private markets. Over 200 billion of public AI-related issuance across different credit channels has happened just in the first five months of this year. We had previously assumed unsecured issuance would be limited by the scale of the largest non-financial issuers confined to investment-grade credit only and largely U.S. dollar denominated. Instead, some hyperscale issuance has now far exceeded even the largest telecom names.

2:12Vishy Tirupattur:Funding has expanded well beyond dollars into euros, pound sterling, Swiss francs, Japanese yen, and Canadian dollar markets. The issuer base has also broadened to include data center REITs and neoclouds, particularly in the high-yield market. The scope of financing has also widened beyond the data center shelves themselves. GPU financing, which we assumed would be funded entirely through equity capital, has begun to migrate into credit markets. Funding is now coming through broadly syndicated loan market and asset-based financing with ABS structure not far behind. Structural innovation illustrates how rapidly the credit ecosystem is adapting to the complexities of demands of AI-driven CapEx.

2:58Vishy Tirupattur:Financings that combine elements of project finance, tranching, residual value guarantees, along with high-yield issuance backed by hyperscaler guaranteed leases, these are innovations that we have never seen before. These structures have expanded the investor base, reduced the funding frictions, and further blurred traditional boundaries between both corporate and project finance and public and private credit markets. At the same time, physical, operational, and political constraints are beginning to shape the pace and the composition of the AI infrastructure build-out, and by extension, the demand for financing.

3:37Vishy Tirupattur:Grid access, power generation equipment, skilled labor, and permitting delays are emerging as significant constraints. These are compounded by political and regulatory frictions at the local, national, and international level. As power availability becomes a gating factor, the AI build-out is likely to pull energy infrastructure financing more tightly into the orbit of AI infrastructure financing. The clear takeaway is this. The CapEx requirements underpinning AI infrastructure are expanding exponentially. And with them, the role of credit markets in financing this build-out. Along the way, there will be winners and losers, periods of adjustment, and a range of physical, financial, and political constraints that shape outcomes on the margin.

4:24Vishy Tirupattur:But the broader trajectory is certain. The scale, duration, and strategic importance of AI infrastructure investments means that the financing of this will remain a defining theme for credit markets and credit investors for years to come. Thanks for listening. If you enjoyed the podcast, please leave us a review wherever you listen and share thoughts on the market with a friend or colleague today the preceding content is informational only and based on information available when created it is not an offer or solicitation nor is it tax or legal advice it does not consider your financial circumstances and objectives and may not be suitable for you

From the publisher

Chief Fixed Income Strategist Vishy Tirupattur takes a look at how credit markets are adapting to fund the new phase of AI capex.

Read more insights from Morgan Stanley.


----- Transcript -----

 

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

Today – The critical question behind the AI-driven capex cycle that is front and center for markets year to date. How is credit market financing this ecosystem evolving? 

It’s Wednesday June 3rd at 2 pm in New York. 

When we first discussed the role of credit markets in financing the AI and data center build-out around the middle of last year, the direction of travel was clear. Realizing the transformative potential of AI requires unprecedented levels of capex. What has really surprised us since is the scale and speed of that spending, both of which have exceeded our expectations by a wide margin. 

The upward revision to capex expectations has been dramatic. A year ago, we projected the combined capex of the five large hyperscalers at roughly $450 billion in both 2026 and 2027. After the first quarter earnings reports, Morgan Stanley’s internet equity analysts, led by Brian Nowak, now expect hyperscaler capex of roughly $800 billion in 2026 and $1.2 trillion in 2027. One data point really captures the surge in the underlying demand for compute. According to OpenRouter, the global weekly token usage, which is a key proxy for compute, has risen by roughly 350 percent since early January, increasing from about 6 trillion tokens to 28 trillion tokens. 

Credit channels for financing this capex have not only been broader and deeper than we anticipated, spanning public and private markets, but have seen remarkable in the structural innovation that is blurring the lines between public and private markets. Over $200bn of public AI-related issuance across the different credit channels has happened just in the first five months of this year. We had previously assumed unsecured issuance would be limited by the scale of the largest non-financial issuers, confined to investment grade credit only, and largely USD denominated. Instead, some hyperscaler issuance has now far exceeded even the largest telecom names; funding has expanded well beyond USD into EUR, GBP, CHF, JPY and CAD markets. The issuer base has also broadened to include data center REITs and neoclouds, particularly in the high-yield market. 

The scope of financing has also widened beyond the data center shells themselves. GPU financing, which we assumed would be funded entirely through equity capital, has begun to migrate into credit markets. Funding is now coming through broadly syndicated loans and asset based financing, with ABS structures not far behind. 

Structural innovation illustrates how rapidly the credit ecosystem is adapting to the complexities of demands of AI-driven capex. Financings that combine elements of project finance, tranching, and residual value guarantees, along with high-yield issuance backed by hyperscaler guaranteed leases – these are innovations that we have never seen before. These structures have expanded the investor base, reduced the funding frictions, and further blurred traditional boundaries – between both corporate and project finance, and public and private credit markets. 

At the same time, physical, operational, and political constraints are beginning to shape the pace and the composition of the AI infrastructure build-out – and, by extension, the demand for financing. Grid access, power generation equipment, skilled labor, and permitting delays are emerging as significant constraints. These are compounded by political and regulatory frictions at the local, national, and international level. As power availability becomes a gating factor, the AI build-out is likely to pull energy infrastructure financing more tightly into the orbit of AI infrastructure financing. 

The clear takeaway is this. The capex requirements underpinning AI infrastructure are expanding exponentially, and with them the role of credit markets in financing this build-out. Along the way, there will be winners and losers, periods of adjustment, and a range of physical, financial, and political constraints that shape outcomes on the margin. 

But the broader trajectory is certain. The scale, duration, and strategic importance of AI infrastructure investment mean that financing of this will remain a defining theme for credit markets and credit investors for years to come. 

Thanks for listening. If you enjoy the podcast, please leave us a review wherever you listen and share Thoughts on the Market with a friend or colleague today.

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