AI spending boom faces productivity gap, economists warn

October 3, 2026 at 10:00 AM2 min

This digest was compiled by AI from multiple sources — links to the originals are below.

Global AI investment has reached historic levels, with data center spending alone projected to top $30 trillion by 2050. Economists warn that broad-based productivity gains remain elusive, raising doubts about whether current valuations can be justified. The funding gap may require entirely new markets to emerge, according to Bain & Company.

Key Facts

Cumulative global spending on data centers could top $30 trillion by 2050, according to PwC.
Anthropic plans to spend $518 billion in coming years, more than 100 times its 2025 revenue, per its IPO prospectus.
US hyperscalers and others in the AI race need to find more than $4.2 trillion of new revenue in the next five years to fund the buildout, Bain & Company said.
JP Morgan estimated US productivity gains would need to be 3% to 5% annually over the next 10 years to justify Nvidia's valuation.
The US Congressional Budget Office baseline expectation is 1.75% annual productivity growth for that period.

Unprecedented Capital Inflows

Never has so much cash flowed into a new technology as is pouring into AI, eclipsing the sums splurged on railways or the internet when those technological revolutions sucked in capital. Cumulative spending globally on data centers alone could top $30 trillion by 2050, according to a projection by PwC, almost matching the value of outstanding US Treasuries. It dwarfs what was spent in the railroad or dotcom booms, even after adjusting for inflation, PwC said. Anthropic, just one of the major firms in the AI race, plans to spend $518 billion in coming years, according to the IPO prospectus seen by Reuters, which is more than 100 times its 2025 revenue. Its backers say AI technology will be more transformational than the advent of steam engines and the industrialization they powered.

Productivity Gains Remain Elusive

JP Morgan wrote in August that broad-based productivity gains in the US, which leads the AI race, remain elusive, raising questions about the sustainability of AI valuations. A Bain & Company study said productivity gains from existing markets would not be enough to justify current outlays and entirely new markets must emerge to close the funding gap. US hyperscalers like Google, Amazon and Microsoft and others in the AI race needed to find more than $4.2 trillion of new revenue in the next five years to fund the buildout, Bain said. The question is whether the applications arrive in time to pay for it, according to the study, published last month.

Valuation and Historical Precedent

Historical precedent suggests that technology-driven booms often end when infrastructure buildouts cease to deliver sufficient returns, JP Morgan wrote. Using the example of Nvidia, the US company whose chips are the backbone of the AI revolution, JP Morgan estimated US productivity gains would need to be 3% to 5% annually over the next 10 years to justify its valuation. That would be a substantial increase from the baseline expectation of the US Congressional Budget Office of 1.75% annual productivity growth for that period.