PwC projects that worldwide spending on data centres might surpass $30 trillion by the year 2050. Anthropic plans to allocate $518 billion over the coming years, according to an IPO prospectus seen by Reuters.
JP Morgan wrote in August that broad-based productivity gains across the United States remain difficult to achieve. A Bain and Company study suggested that entirely new markets must emerge to bridge the funding gap.
Bain noted that US hyperscalers and other participants in the AI race require more than $4.2 trillion in new revenue within the next five years to fund expansion. To justify Nvidia's current valuation, JP Morgan estimated that US productivity gains would need to reach 3% to 5% annually over the next decade.
Conversely, the US Congressional Budget Office anticipated an annual productivity growth rate of 1.75% for the next ten years. Columbia Business School economist Stijn Van Nieuwerburgh estimated that investment in the US alone could reach as high as about $9 trillion between 2025 and 2032.
Stijn Van Nieuwerburgh further calculated that the US AI sector would need to generate approximately $3.55 trillion in yearly revenue by 2032 to achieve a 10% return on investment. At a summit at UC Berkeley in August, Jasjeet Sekhon told attendees that recursive self-improvement formed a key element of the investment thesis.
Diane Coyle stated that the productivity boost from previous revolutionary technologies typically took between 10 and 50 years to fully impact the economy. Anthropic's economics team modeled a growth rate of 2.4% for 2030 under a modest AI impact scenario.
Researchers at Stanford University reported in August that employment for workers aged 22 to 25 in industries exposed to AI was 19% lower than for jobs AI found difficult to replicate.
