AI is a key driver of U.S. economic growth, contributing 39% to expansion

Artificial intelligence (AI) has emerged as a critical engine for U.S. economic expansion, accounting for 39% of the nation's growth in the first three quarters of last year, according to an analysis by the Bank of Korea's New York office. The proliferation of AI technology is driving a significant increase in demand for computing power and spurring substantial investments in data centers across the United States.

The report, titled 'U.S. Economic Outlook for the Second Half of 2026 and Key Issues,' highlights that the U.S. currently hosts 4,378 data centers, representing 37.5% of the global total. Furthermore, approximately 2,700 new data centers are either under construction or in the planning stages. This massive build-out is largely driven by big tech companies' capital expenditures, with AI-related sectors boosting overall growth rates by an estimated 1 percentage point in the first three quarters of last year.

Looking ahead, the Bank of Korea's office anticipates that large-scale AI investments will continue for an extended period. This sustained growth is attributed to the explosive increase in computing demand fueled by the spread of agent-based AI, coupled with rising costs for building AI infrastructure. Factors contributing to these higher costs include the expense of specialized equipment, power facility upgrades, and a shortage of skilled labor.

Additionally, the relatively short economic lifespan of key AI components, such as semiconductor chips and servers, estimated at only two to three years due to heat issues and performance improvements, necessitates frequent equipment replacement, further driving capital expenditure. The report also notes the rapid expansion of project financing, particularly through private credit, to support this AI infrastructure boom. However, it cautions that a slowdown in AI demand or delays in monetization could lead to increased credit risks. The analysis concludes by emphasizing the need to continuously monitor constraints on AI infrastructure investment, including power supply capacity, supply chain issues, and regulatory environments.