Morgan Stanley projects that global capital expenditure for data-center construction will reach approximately $2.9 trillion by 2028, driven by various funding sources, including $1.4 trillion from hyperscaler cash flows and a substantial reliance on debt financing. This reliance on credit is particularly concerning, as highlighted by Professor Aswath Damodaran, who notes that while the dot-com bubble was primarily equity-funded, the current AI infrastructure boom is significantly supported by debt. Damodaran warns that should a market correction occur, the repercussions may extend beyond shareholders to affect broader society, due to the extensive level of debt incurred by companies in the quest for AI advancement, drawing parallels to the financial crisis of 2008.

Rohan Paul: Rohan Paul is a technology and AI commentator active on social media as @rohanpaul_ai, where he shares and discusses developments in artificial intelligence and related markets. He often highlights reports and analyses relevant to AI investment themes. In this news, he is quoted as the source sharing the Morgan Stanley estimate on data-center capital expenditures and the associated funding breakdown.
Morgan Stanley: Morgan Stanley is a global financial services firm specializing in investment banking, institutional securities, wealth management, and investment management. It produces in-depth research and analysis on major economic and industry trends, including technology infrastructure. In this news, the firm issued an estimate on the scale of upcoming data-center construction spending tied to AI development and outlined its projected funding sources.
Aswath Damodaran: Aswath Damodaran is a professor of finance at NYU Stern School of Business and a leading expert in corporate valuation, capital structure, and investment analysis. He frequently comments on market cycles, bubbles, and the implications of large-scale corporate spending. In this news, he is quoted contrasting the current AI-driven infrastructure buildout with the dot-com era, highlighting differences in funding methods and potential broader economic consequences.

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{
“AI Infrastructure”: “Significant technology investments are fueling a large-scale development of data centers and related facilities.”,
“Debt Financing Trends”: “A notable portion of AI-related capital expenditure is being financed through debt and private credit channels rather than just equity.”,
“Historical Comparisons”: “Observers are drawing parallels between the present AI boom and previous technology cycles, focusing on how funding mechanisms may impact the potential for market adjustment.”
}
`