JP MORGAN CHASE(US:JPM) 美股研究社·2025-11-12 12:59Core Viewpoint - Morgan Stanley warns that the $5 trillion AI boom will "squeeze" every credit market, with a projected funding requirement of $5 trillion to $7 trillion for AI data center construction over the next five years [2][3]. Funding Requirements - The report predicts that the investment-grade bond market will need to provide approximately $1.5 trillion, while leveraged finance markets will contribute around $150 billion, and data center asset securitization can only handle $30 billion to $40 billion annually, leaving a $1.4 trillion funding gap that will require private credit and government funds to fill [3][23]. Capital Market Dynamics - The construction of AI and data centers is expected to be a "remarkable and sustained capital market event," with a need for an additional 122 GW of data center infrastructure capacity from 2026 to 2030, and a more optimistic forecast suggesting a growth of 144 GW in the next three years [7][10]. Energy Constraints - Physical constraints, particularly in electricity supply, pose significant challenges, with natural gas turbine delivery times extending to 3-4 years and nuclear power plant construction taking over ten years [11]. Funding Sources - Major tech companies generate over $700 billion in operating cash flow annually, with an estimated $300 billion directed towards AI and data center investments [16]. - The high-grade bond market is expected to absorb about $300 billion in AI-related bonds within the next year, totaling $1.5 trillion over five years [17]. - The leveraged finance market can provide around $150 billion in funding over the next five years, while the securitization market is projected to absorb $30 billion to $40 billion annually [20][22]. Private Credit and Alternative Capital - There remains a significant funding gap of approximately $1.4 trillion that will primarily be filled by private credit and alternative capital, with the private credit market holding around $466 billion in capital [23][24]. Historical Context and Risks - The report draws parallels between the current AI investment frenzy and the telecom bubble of the early 2000s, highlighting the potential for a similar outcome if revenue growth does not keep pace with investment [28][29]. - Two core risks identified are monetization risk, requiring $650 billion in new revenue annually to achieve a 10% return, and disruptive technology risk, where advancements could render existing investments obsolete [30][31]. Conclusion - The report emphasizes that the wave of AI infrastructure development is irreversible and will inject unprecedented vitality into capital markets, but not all participants will emerge as winners, necessitating a careful understanding of capital flows and the identification of companies with sustainable competitive advantages [32].