Blackstone president calls for more equity to fund AI buildout as debt risks mount

The staggering financial demands of the artificial intelligence boom are rapidly outpacing traditional debt markets, setting the stage for a massive shift toward equity financing, according to industry heavyweights speaking at a premier global financial gathering.

The warning was delivered on Tuesday by Jon Gray, president and chief operating officer of Blackstone Inc., during the high-profile Global Financial Leaders’ Investment Summit in Hong Kong, China. The annual event, convened by the Hong Kong Monetary Authority, brought together approximately 280 global financial leaders—including roughly 120 group chairs and chief executive officers—to deliberate over the outlook for international markets, the broader global economy, and the profound economic ramifications of rapid advances in artificial intelligence technology.

Gray told attendees that the unprecedented scale of capital required to power the artificial intelligence infrastructure buildout is creating dangerous concentration risks for traditional debt investors, affecting both the sector as a whole and individual corporate balance lines. Because lenders face structural limitations on their financial upside—with their returns largely confined to fixed interest payments and eventual principal repayments—they are absorbing mounting exposure without sharing directly in the explosive equity growth experienced by successful technology companies.

"There’s going to be more equity needed across this space to keep up with these enormous demands," Gray emphasized during his panel appearance, underscoring that the sheer velocity of capital expenditure will necessitate alternative funding structures to protect lenders and stabilize the broader financial ecosystem.

Echoing these concerns during the same panel session, Pimco CEO Emmanuel Roman delivered an even starker caution, warning investors that the sheer scale of artificial intelligence financing could eventually prove to be too massive for global debt markets to absorb cleanly. Roman pointed to broader industry figures, noting that artificial intelligence-related capital spending could skyrocket to approximately $10 trillion over the next five years, an estimate originally put forward by General Atlantic CEO Bill Ford.

To put that staggering trajectory into perspective, Roman noted that roughly $550 billion in artificial intelligence-related debt had already been issued in various forms over the course of the year. Even when factoring in a diversified mix of equity and debt financing, the total volume of capital required remains gigantic, especially when compared against the global corporate bond market, which stands at roughly $20 trillion.

"At some point in time, it’s going to be too much," Roman warned, highlighting the structural strains that tech-driven capital expenditure is placing on institutional portfolios and global liquidity pools.

Complementing these financial warnings, a comprehensive report released on Monday by Goldman Sachs estimated that global data center demand alone will necessitate roughly $8.5 trillion in capital spending over the coming five-year period, illustrating the monumental physical and financial footprint required to sustain the artificial intelligence revolution.

To navigate these unprecedented liquidity demands, Gray argued that financing the ongoing buildout will require an intricate combination of public markets, traditional commercial banks, and private capital sources. Companies at the forefront of the technological shift are already beginning to explore and deploy structured transactions designed to cap and limit the absolute volume of debt they take on their balance sheets. In addition to external financing, substantial portions of the necessary spending will continue to be fueled directly by the robust internal cash flows generated by major technology hyperscalers.

"The creativity is needed because the scale of capital is enormous," Gray noted, pointing to the financial engineering required to bridge the gap between supply and demand in the digital infrastructure space.

Despite the formidable financing challenges and structural market warnings, Gray maintained an inherently bullish outlook on the underlying fundamentals of artificial intelligence infrastructure. He reported that actual enterprise demand for advanced computing power continues to run well ahead of available supply, driven by tangible productivity gains across industries.

Illustrating this surging commercial appetite, Gray noted that spending on artificial intelligence models across Blackstone’s own extensive portfolio of companies had multiplied twentyfold over the past year alone. Business enterprises are increasingly realizing measurable financial benefits from deploying these technologies across practical operational use cases, including software coding, enhanced customer engagement, and automated content creation.

However, translating that insatiable commercial demand into operational reality remains an uphill battle. Gray pointed out that securing appropriate physical sites, navigating complex regulatory permitting processes, sourcing scarce advanced semiconductors, guaranteeing reliable electrical power, and locking down sufficient capital continue to present significant hurdles for developers and technology giants alike. As the artificial intelligence infrastructure buildout accelerates, the ability to balance these formidable operational bottlenecks with sustainable financial structures will ultimately dictate the pace of future growth.