AI Investment Boom May Be Starving Other Sectors of Capital

The Scale of AI Capital Deployment

Wall Street analysts now estimate that Amazon, Microsoft, Alphabet, Nvidia, and Meta could collectively spend as much as $1.4 trillion on AI-related infrastructure by 2027, according to economist Dambisa Moyo writing for Project Syndicate. Research firm Gartner projects global AI spending will reach $2.5 trillion in 2026 alone.

This capital is flowing into data centers, advanced networking equipment, and electricity infrastructure across the United States. Apollo Global Management's chief economist notes that hyperscaler capital expenditure is expected to reach roughly 3% of GDP annually between 2027 and 2029—up sharply from 0.3% in 2019 and 1.4% in 2025.

Why It Matters

The AI investment surge is colliding with declining household savings and rising interest rates, creating conditions where capital-intensive industries may struggle to secure financing. If borrowing costs continue climbing as AI firms compete for limited capital, the result could be an "innovation winter" in sectors like biotech, greentech, and manufacturing—potentially constraining broader economic growth even as AI promises productivity gains.

Evidence of Capital Competition

Several indicators suggest AI may be crowding out other investment. In 2025, AI accounted for 65.4% of venture capital deal value in the United States. Startups in greentech and social impact investing are finding it harder to attract funding, according to AI engineer Abhay Gupta's 2024 warning.

The five largest hyperscalers issued $132 billion in debt during the first eight months of 2026—compared to an annual average of $35 billion between 2020 and 2024. Vanguard estimates total AI-related debt issuance could reach $300-570 billion for the full year.

Meanwhile, US household savings rates have fallen from 3.8% to 3% since ChatGPT's November 2022 release, even as AI investment has surged. This contrasts sharply with the "savings glut" era during Ben Bernanke's Federal Reserve tenure, when abundant savings kept interest rates low.

Goldman Sachs economists Jessica Rindels and David Mericle have noted the risk that AI could starve other productive sectors of capital. Bank of England Governor Andrew Bailey recently warned of a potential AI investment bubble collapse that could trigger a major financial downturn.

The Counterarguments

The crowding-out thesis faces three significant challenges. First, Bureau of Economic Analysis data shows gross private investment as a share of US GDP has remained broadly stable—AI may be consuming more investment, but not at the expense of overall investment levels.

Second, rising interest rates may reflect multiple factors beyond AI demand, including the Iran war and renewed inflation concerns following energy price spikes.

Third, the Jevons paradox suggests AI could actually stimulate investment across sectors. By increasing productivity and lowering costs, AI might boost demand for goods and services, prompting companies to invest more in power generation, utilities, financial services, and cloud computing.

Current Assessment

Moyo concludes that AI appears to be crowding out investment at the margins rather than across the board. Capital and resources are clearly being diverted—Intel has indicated semiconductor supply is shifting toward AI and away from PCs, while companies like Otis and Lennar report skilled-labor shortages delaying projects. However, there is not yet sufficient evidence to conclude AI is dragging down overall investment or economic growth.

The analysis was originally published by Project Syndicate, with Moyo noting that the AI investment cycle now ranks ahead of historical booms including the mid-19th-century railroad expansion, the interstate highway system construction from 1955 to 1970, and the Apollo space program.