At the International Financial Leaders Investment Summit, Morgan Stanley CEO Ted Pick stated that capital expenditure in the artificial intelligence (AI) sector could reach $10-15 trillion over the next decade, cementing AI's position as the most significant economic transformation since the birth of the internet.
He estimated that leading hyperscale technology companies could deploy $800 billion to $1 trillion annually on data centers and computing investments over a 7-12 year period.
Pick described the current deployment as still being in its formative stage, saying "we are probably in the second inning of a nine-inning game."
Pick argued that comparing the spending to stock valuations, the total cost of $10-15 trillion, while enormous, is not unreasonable when measured against the S&P 500's market capitalization of approximately $70 trillion, with $2-3 trillion already committed or in use.
He estimated that the productivity dividend from AI could boost U.S. real GDP growth by 50-70 basis points annually.
However, PIMCO CEO Emmanuel Roman warned that AI-related financing could grow to approximately $10 trillion over the next five years, ultimately reaching excessive levels.
He estimated that the AI industry may generate approximately $2 trillion in annual financing demand to fund capital expenditures, while the U.S. bond market is approximately $12 trillion in size.
Emmanuel noted that the scale of financing will eventually "become too large" and that "there will come a time when the tide goes out, and when that happens, something somewhere will break," with rising U.S. interest rates, Middle East wars, and even a eurozone crisis all potentially triggering a turning point.
State Street Chairman and CEO Ron O'Hanley stated that it is currently "difficult" to view AI as a bubble, as market demand supports substantial investment. "These data centers are not being built randomly — there are actual orders behind them, and in most cases, there are real companies behind them," he said.
He believes the real question is whether AI will eventually become so efficient that all the capacity currently being built becomes unnecessary.
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