The artificial intelligence infrastructure buildout will need more equity financing as lenders become increasingly exposed to the companies driving it, Blackstone President and Chief Operating Officer Jon Gray said on Tuesday. Speaking at the Hong Kong Monetary Authority's Global Financial Leaders' Investment Summit, Gray said the scale of capital required for AI is creating concentration risks for debt investors, both across the sector and at individual companies.
Unlike shareholders, who can benefit from a company's growth, lenders have limited upside because their returns are largely confined to interest and principal repayments, he said.
The summit in Hong Kong brings together around 280 global financial leaders, including roughly 120 group chairs and CEOs, with the outlook for markets, the global economy and rapid advances in technology among the big themes.
"There's going to be more equity needed across this space to keep up with these enormous demands," Gray said.
Speaking on the same panel, Pimco CEO Emmanuel Roman warned investors that the scale of AI financing could prove to be "too much" for markets to absorb. Roman said AI-related capital spending could reach around $10 trillion over the next five years, citing an estimate by General Atlantic CEO Bill Ford. He added that about $550 billion in AI debt had been issued in various forms so far this year.
Even with a mix of equity and debt financing, the amount required would be "gigantic," Roman said, comparing it with a global corporate bond market of roughly $20 trillion. "At some point in time, it's going to be too much," he said.
Goldman Sachs wrote in a report on Monday that global data centre demand will require about $8.5 trillion in capital spending over the next five years.
Gray said financing the buildout would require a combination of public markets, banks and private capital, with companies increasingly turning to structured transactions to limit the amount of debt they take on. Cash generated by hyperscalers would also fund part of the spending, he said.
"The creativity is needed because the scale of capital is enormous," Gray said.
Despite those financing challenges, Gray remained bullish on AI infrastructure, saying demand for computing power was "running well ahead of supply." Spending on AI models across Blackstone's portfolio companies had risen 20-fold over the past year as businesses saw financial benefits from uses including coding, customer engagement and content creation, he said.
Meeting that demand remains difficult, however, as securing sites, permits, chips, power and capital becomes more challenging, according to Gray.
Analysis
Why This Matters
- The people financing AI data centres are publicly flagging a shift in how the buildout gets paid for, which affects the cost and availability of capital for AI companies and their backers.
- Lenders' limited upside, as described by Gray, matters to anyone holding AI-related debt or credit exposure, since concentration risk at individual companies and across the sector is a portfolio question, not just a company one.
- The competing estimates aired on the same panel (around $10 trillion of AI capital spending cited by Roman, about $8.5 trillion of data centre spending in Goldman's report) frame how large the financing gap is seen to be by major market participants.
Background
Blackstone is one of the world's largest alternative asset managers, and Pimco is a major fixed-income investor, so both sit close to the capital flows behind the AI buildout. The Hong Kong Monetary Authority's Global Financial Leaders' Investment Summit is an annual gathering of bank and asset management executives; this year's agenda includes the market and economic outlook alongside rapid advances in technology. The discussion comes as the data centre construction wave has become one of the largest draws on both equity and debt capital in global markets.
Key Perspectives
Jon Gray, Blackstone: says more equity is needed across the AI space to meet demand, that lenders face concentration risk with limited upside, and that financing will need public markets, banks and private capital combined, including structured transactions and hyperscaler cash; he remains bullish on AI infrastructure because demand for computing power is running ahead of supply.
Emmanuel Roman, Pimco: warned that the scale of AI financing could prove "too much" for markets to absorb, citing an estimate of around $10 trillion in AI capital spending over five years and about $550 billion of AI debt issued this year, against a global corporate bond market of roughly $20 trillion.
Goldman Sachs: wrote in a report on Monday that global data centre demand will require about $8.5 trillion in capital spending over the next five years.
What to Watch
- Whether AI-related borrowers shift toward equity and structured transactions, as Gray expects, and what that does to debt issuance volumes.
- The pace of AI debt issuance into next year, given Roman's warning that the market's capacity to absorb it is finite.
- Signs of strain at individual companies as sites, permits, chips and power become harder to secure, the constraints Gray identified.
Checked
12 claims in this story checked against 1 source: 12 supported.
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- SupportedGray said, “There's going to be more equity needed across this space to keep up with these enormous demands.”Finance: “There’s going to be more equity needed across this space to keep up with these enormous demands.”
- SupportedRoman said AI financing could prove to be “too much” for markets to absorb.Finance: “Pimco CEO Emmanuel Roman warned investors that the scale of AI financing could prove to be "too much" for markets to absorb.”
- SupportedGray said, “The creativity is needed because the scale of capital is enormous.”Finance: ““The creativity is needed because the scale of capital is enormous," Gray said.”
- SupportedGray said demand for computing power was “running well ahead of supply.”Finance: “Gray remained bullish on AI infrastructure, saying demand for computing power was “running well ahead of supply.””
- SupportedGray said AI infrastructure will need more equity financing as lenders become more exposed to the companies driving the buildout.Finance: “The artificial intelligence infrastructure buildout will need more equity financing as lenders become increasingly exposed to the companies driving the buildout, Blackstone President Jon Gray said Tuesday.”
- SupportedGray said the capital required for AI is creating concentration risks for debt investors across the sector and at individual companies.Finance: “Gray said the scale of capital required for AI is creating concentration risks for debt investors, both across the sector and at individual companies.”
- SupportedGray spoke at the HKMA's Global Financial Leaders' Investment Summit in Hong Kong on Tuesday.Finance: “Speaking at the Hong Kong Monetary Authority’s Global Financial Leaders’ Investment Summit, Gray said the scale of capital required for AI”
- SupportedRoman said AI-related capital spending could reach around $10 trillion over the next five years, citing Bill Ford's estimate.Finance: “Roman said AI-related capital spending could reach around $10 trillion over the next five years, citing General Atlantic CEO Bill Ford's estimate.”
- SupportedRoman said about $550 billion in AI debt had been issued in various forms so far this year.Finance: “He added that about $550 billion in AI debt had been issued in various forms so far this year.”
- SupportedRoman compared the required financing with a global corporate bond market of roughly $20 trillion.Finance: “Even with a mix of equity and debt financing, the amount required would be “gigantic,” Roman said, comparing it with a global corporate bond market of roughly $20 trillion.”
- SupportedGoldman Sachs said global data centre demand will require about $8.5 trillion in capital spending over the next five years.Finance: “Global data center demand will require about $8.5 trillion in capital spending over the next five years, Goldman Sachs wrote in a report Monday.”
- SupportedSpending on AI models across Blackstone's portfolio companies had risen 20-fold over the past year.Finance: “Spending on AI models across Blackstone’s portfolio companies had risen 20-fold over the past year”
