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Financial leaders split on AI spending outlook at Hong Kong summit

Investment executives raised concerns about valuations and returns, while bank chiefs cited computing demand and potential gains in economic growth.

By Tomasz Lindqvist

Financial charts displayed beside a computer keyboard
Photo: TNW (Financial Times)

The scale of artificial intelligence investment divided financial executives meeting in Hong Kong, Bloomberg reported. Fund managers questioned whether returns would justify spending, while banking leaders emphasized demand and the potential economic benefits.

Morgan Stanley chief executive Ted Pick put potential AI development spending at US$10 trillion to US$15 trillion over the next decade, according to The Standard. He said it could lift real GDP growth by 0.5 to 0.7 percentage points, though projects with fragile finances would face failure.

Pimco chief executive Emmanuel Roman sounded more cautious, telling Bloomberg that financing for AI could amount to about US$10 trillion over five years and would eventually become excessive. Possible catalysts for a downturn included increasing US interest rates, conflict in the Middle East or eurozone turmoil, he said.

Bain Capital chairman John Connaughton questioned whether investors could achieve returns matching the elevated prices of some AI assets, Bloomberg reported. Jenny Johnson, Franklin Templeton’s chief executive, said leading cloud companies were shifting toward business models requiring substantial capital.

Goldman Sachs chief executive David Solomon said computing demand continued to outstrip available capacity. He expected businesses developing AI applications to capture value over the longer term. Blackstone president Jon Gray also anticipated further AI-driven investment and capital demand.

The Hong Kong Monetary Authority’s Global Financial Leaders’ Investment Summit brings together roughly 280 senior financial figures. It followed October’s steep technology-share losses, when corporate results, including Alphabet’s latest quarter, renewed doubts over the returns from AI expenditure.

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