Currently, the wave of Technology driven by artificial intelligence (AI) continues to sweep across the globe and remains a core issue in markets across industries and regions. Morgan Stanley's Global Head of Algo Strategy, Vishwanath Tirupattur, has carefully calculated how much the upcoming AI wave will cost in the latest report...
According to reports from the Financial Association on July 21 (Editor: Xiaoxiang), the wave of Technology driven by artificial intelligence (AI) continues to sweep across the globe and remains a core issue in markets across industries and regions. In this regard, Morgan Stanley's Global Head of Algo Strategy, Vishwanath Tirupattur, has carefully calculated how much the upcoming AI wave will cost in the latest report...
Tirupattur pointed out that the transformative potential of the AI wave depends on large-scale capital expenditure, with data centers being at its core. According to Morgan Stanley's predictions, global data center expenditure will reach approximately $2.9 trillion by 2028, of which $1.6 trillion will be for hardware (chips/servers) and $1.3 trillion will be for building data center infrastructure, including Property/A-REIT, construction costs, and maintenance expenses. On an annual basis, this means that investment demand in 2028 will exceed $900 billion.
For reference, the total capital expenditure of all companies in the S&P 500 Index in 2024 is only about $950 billion.
Such a massive potential expenditure will evidently have significant macroeconomic impacts. Morgan Stanley economists predict that investment spending related to data center construction and power generation will contribute 40 basis points to the growth of U.S. real GDP during 2025-26.
From any perspective, the capital needed to support such investment is extremely large, making efficient and scalable capital mobilization increasingly critical. Morgan Stanley also explores alternative capital pathways for financing this expenditure in a detailed report.
The key conclusion of the report is that the credit market—whether secured, unsecured, public, or private—will play an increasingly important role in financing data centers.
The world needs to raise $1.5 trillion to 'bet on tomorrow.'
It is important to clarify that capital expenditure related to artificial intelligence and data centers has actually been ongoing for several years. The expenditure of just the super-scale enterprises has increased from about 125 billion dollars two years ago to approximately 200 billion dollars in 2024, with the market widely expecting it to exceed 300 billion dollars by 2025.
The funding source for these expenditures has previously relied on the internal operating cash flow of super-scale enterprises.
However, Morgan Stanley's stock analysts expect that the demand for investment in data centers will rise sharply in the coming years. While the cash flow from super-scale enterprises will still be a key capital source for funding data center-related expenditures, considering cash accumulation and shareholder capital returns, Morgan Stanley believes that these alone will no longer be sufficient.
According to Morgan Stanley analysts' predictions, super-scale enterprises may have 1.4 trillion dollars of capital expenditure funded by their cash flow, which will leave a financing gap of up to 1.5 trillion dollars.
Morgan Stanley believes that the broader credit market (covering various types of public and private markets) will play a role as a more efficient provider of capital in filling this gap. The credit market has a large and growing pool of disposable funds and offers attractive real yield, which is appealing to a sticky group of end investors seeking scalable, high-quality asset exposure that can provide diversified returns (for example, insurance funds, sovereign wealth funds, pension funds, endowment funds, and high-net-worth retail investors). Morgan Stanley believes this match between funding demand and investment demand will pave the way to fill the 1.5 trillion dollar financing gap.
Morgan Stanley estimates the scale of various financing channels as follows:
Unsecured corporate bond issuance by technology industry issuers (about 200 billion dollars); securitized markets such as ABS (Asset-Backed Securities) and CMBS (Commercial Mortgage-Backed Securities) (about 150 billion dollars); private credit markets in the form of asset-backed financing (about 800 billion dollars); and other capital sources such as sovereign funds, private equity, venture capital, and bank loans (about 350 billion dollars).
Among them, Morgan Stanley believes that private capital—especially credit—will play a key role in filling most of the remaining funding gap, as it just so happens to be at the intersection of a higher interest rate environment, significant expansion of AUM (Assets Under Management), and the complex, globalized, and customized financing needs required for AI development.
