Episode summary
The New AI Credit Playbook
Thoughts on the Market (Morgan Stanley)
· · Hosts: Vishy Tirupattur
Summary
Vishy Tirupattur argues that the AI capex cycle has accelerated far beyond what markets expected, forcing credit markets to adapt quickly. Morgan Stanley had once projected combined capex for the five large hyperscalers at about $450 billion in 2026 and 2027, but after first-quarter results analysts now expect roughly $800 billion in 2026 and $1.2 trillion in 2027. He also points to OpenRouter data showing global weekly token usage rising about 350% since early January, a sign of surging compute demand.
He says the financing ecosystem has broadened rapidly across public and private markets, with more than $200 billion of public AI-related issuance in just the first five months of the year. What is new, in his view, is not only the scale but the structure: issuance has expanded into multiple currencies, the issuer base now includes data center REITs and neoclouds, and GPU financing is increasingly being funded through broadly syndicated loans and asset-based finance. He describes these instruments as innovations that blur the line between corporate and project finance.
Tirupattur also warns that physical and political constraints will shape how fast the buildout proceeds. Grid access, power equipment, labor, and permitting are becoming binding constraints, which may pull energy infrastructure financing closer to AI infrastructure finance. Even so, he says the broader trajectory is clear: AI infrastructure spending will remain a defining credit theme for years.
Key takeaways
- Tirupattur says hyperscaler capex expectations jumped from about $450 billion to $800 billion in 2026 and $1.2 trillion in 2027.
- He says more than $200 billion of public AI-related issuance has already come through credit markets in the first five months of 2026.
- He argues financing is spreading beyond dollars into euros, sterling, Swiss francs, yen and Canadian dollars.
- He says GPU financing is migrating into broadly syndicated loans and asset-based financing, not just equity.
- He expects grid access, power equipment, labor and permitting to become key constraints on the AI buildout.
Notable quotes
“How is the credit market financing of this ecosystem evolving? It's Wednesday, June 3rd at 2 p.m. in New York”
“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”
“After the first quarter earnings reports, mortgage handling internet equity analysts led by Brian Noak now expect hyperscaler capex of roughly 800 billion in 2026 and 1.2 trillion in 2027”
“Over 200 billion of public AI related issuance across different credit channels has happened just in the first 5 months of this year”
“These are innovations that we have never seen before”
How the episode opens
Welcome to thoughts on the market. I am Rishi Tupaturalis chief fixed income strategist. Today the critical question behind the AIdriven 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 trade markets in financing the AI and data center buildout 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 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, mortgage handling internet equity analysts led by Brian Noak 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 Open Router, 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. Trade 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 5 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 US dollar denominated.
From the episode’s captions: roughly the first two minutes, lightly cleaned. Keep watching on YouTube →
Topics
- ai capex
- credit markets
- fixed income
Watch the episode
Watch “The New AI Credit Playbook” on YouTube
Summary, takeaways and quote selection by Octagon. Quotes are short excerpts; the full conversation is in the episode.
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