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Ray Dalio warns AI investment 'bubble' may face pressure from higher rates and tighter liquidity

Bridgewater Associates founder Ray Dalio told the Forbes Global CEO Conference in Singapore that investment in artificial intelligence is exhibiting classic bubble characteristics, driven largely by debt-funded spending.

Ray Dalio warns AI investment 'bubble' may face pressure from higher rates and tighter liquidity

Ray Dalio, founder of Bridgewater Associates, said at the Forbes Global CEO Conference in Singapore that investment around artificial intelligence (AI) is displaying characteristics of a classic bubble and could soon come under significant pressure due to the current macroeconomic environment.

Dalio noted that much of the AI development is being financed with debt: large technology companies are spending "hundreds of billions of dollars" on AI infrastructure and are increasingly relying on borrowing. Rising interest rates and bond yields, which have climbed to multi-year or decade highs in many markets, make raising such finance more expensive and can render the debt burden unsustainable.

At the same time, he observed that equity markets have so far continued to rise, with gains and yields concentrated in a handful of leading technology stocks. That combination—debt-fueled investment on one side and concentrated equity performance on the other—is, in his view, a typical sign of a bubble phase.

Dalio added that the bursting of such a bubble need not be triggered solely by higher rates or pricier financing. Other events, such as the introduction of a wealth tax or any liquidity shock that forces investors to convert unrealized paper gains into cash, could precipitate a correction. He emphasized that many market participants hold large paper wealth that must be realized through asset sales before it can be spent or redeployed, and markets often turn at that point.

While Dalio said we are not yet in the terminal phase of a collapse, he believes the turning point could be near. His comments serve as a warning to investors and policymakers about the scale of AI-related spending and the financing structures that could have broader macroeconomic implications.

This article does not constitute investment advice.