Alphabet’s chief investment officer responds to Jefferies warning that the most likely outcome of the AI boom is massive U.S. capital destruction

Alphabet's Chief Investment Officer Ruth Porat addressed concerns raised by Jefferies regarding the potential for massive U.S. capital destruction as a result of the AI boom. According to analyst estimates, over $720 billion of capital expenditures are projected to be spent this year on AI infrastructure by companies like Amazon, Alphabet, Microsoft, and Meta.

Porat confirmed that Alphabet intends to spend "significantly more" in 2027, with capital expenditures this year expected to be "more than double" the $91.4 billion spent in 2025.

Porat emphasized that the AI buildout is still in its early phases relative to the eventual economic value Alphabet believes AI can drive. She acknowledged that debt is fueling the AI buildout, with private credit funds such as Blue Owl, Apollo, and KKR becoming a growing source of funding for AI-related companies. In Q2, Alphabet posted negative free cash flow for the first time since its 2004 IPO, with long-term debt rising to about $98 billion by the end of June.

Jefferies' Chris Wood warned that the most likely long-term outcome of the AI boom is massive capital destruction in the U.S. due to cheaper Chinese open-source models threatening to commoditize large language models and eroding the economics behind America's AI spending. However, Porat disagreed, arguing that companies that add differentiated value to open-weight models will find customers willing to pay for their services.

Porat has observed previous bubbles, including the dot-com era and the 2008 financial crisis, and believes that companies using AI to build truly differentiated experiences will be the winners. She urged businesses to identify their greatest source of vulnerability early and fortify against it, as opposed to simply adding more AI. Despite the potential systemic economic risks of overbuilding, Porat stated that Alphabet will continue to invest heavily in AI due to its conviction in the long-term economic upside.