The promise of generative AI technology to revolutionize companies, industries, and societies has led tech giants and others to spend an estimated $1tn on capital expenditures in the coming years. These investments include significant outlays for data centers, chips, other AI infrastructure, and the power grid. However, this spending has yet to show substantial results.
The question of whether this massive expenditure will ever yield benefits in terms of AI returns is a topic of intense debate. The implications for economies, companies, and markets if it does—or if it doesn’t—are significant and far-reaching.
Some experts, like MIT’s Daron Acemoglu and Goldman Sachs’ Jim Covello, are skeptical. Acemoglu sees only limited US economic upside from AI over the next decade. Covello argues that the technology isn’t designed to solve the complex problems that would justify the costs, which may not decline as many expect.
However, others like Goldman Sachs’ Joseph Briggs, Kash Rangan, and Eric Sheridan remain more optimistic about AI’s economic potential and its ability to ultimately generate returns beyond the current “picks and shovels” phase, even if AI’s “killer application” has yet to emerge.
Despite these concerns and constraints, there is still room for the AI theme to run, either because AI starts to deliver on its promise, or because bubbles take a long time to burst. Given the focus and architecture of generative AI technology today, truly transformative changes won’t happen quickly and few—if any—will likely occur within the next 10 years.
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