Analysis suggests hyperscalers are slowing AI investment mainly because they are running out of cash, not because of technical risks.
Professor Kim Kwang-seok explained that the main reason AI hyperscalers are scaling back their AI-related investments is not the surface-level explanations such as AI risks or regulatory debates.
He stressed that the core of corporate decision-making ultimately comes down to finances: free cash flow has run dry and turned negative, making it difficult to execute new investments.
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