While AI-related spending adds a significant 0.4% to U.S. GDP, its net economic impact is much smaller. A large portion of this investment flows out of the country to pay for imported technology and hardware, significantly reducing the direct domestic benefit of the AI spending boom.
While there's a popular narrative about a US manufacturing resurgence, the massive capital spending on AI contradicts it. By consuming a huge portion of available capital and accounting for half of GDP growth, the AI boom drives up the cost of capital for all non-AI sectors, making it harder for manufacturing and other startups to get funded.
A recent Harvard study reveals the staggering scale of the AI infrastructure build-out, concluding that if data center investments were removed, current U.S. economic growth would effectively be zero. This highlights that the AI boom is not just a sector-specific trend but a primary driver of macroeconomic activity in the United States.
While gross spending on AI appears to be a major growth driver, its net contribution to the US economy is significantly smaller. A large portion of AI-related hardware and software is imported, meaning the immediate GDP impact is diluted. AI's more substantial economic benefit is expected to manifest through longer-term productivity gains.
Traditional metrics like GDP fail to capture the value of intangibles from the digital economy. Profit margins, which reflect real-world productivity gains from technology, provide a more accurate and immediate measure of its true economic impact.
For 2026, AI's primary economic effect is fueling demand through massive investment in infrastructure like data centers. The widely expected productivity gains that would lower inflation (the supply-side effect) won't materialize for a few years, creating a short-term inflationary pressure from heightened business spending.
The tangible economic effect of the AI boom is currently concentrated in physical capital investment, such as data centers and software, rather than widespread changes in labor productivity or employment. A potential market correction would thus directly threaten this investment-led growth.
A surge in business technology investment was misinterpreted as an AI-powered economic boom. It more likely reflected companies front-loading purchases of semiconductors and electronics to avoid paying impending 25% tariffs, rather than a fundamental acceleration in AI-related capital expenditure.
Economists forecast that the combined effect of direct investment in AI infrastructure (data centers, chips) and resulting productivity gains will add between 40 and 45 basis points to U.S. GDP growth over 2026-2027. This represents a significant contribution to the overall economic growth outlook.
AI's contribution to US economic growth is immense, accounting for ~60% via direct spending and indirect wealth effects. However, unlike past tech booms that inspired optimism, public sentiment is largely fearful, with most citizens wanting regulation due to job security concerns, creating a unique tension.
Despite massive AI-related investment, the net effect on US GDP is minimal. This is because the necessary hardware is largely imported, and accounting rules treat semiconductors as intermediate inputs, not final investment, obscuring their direct contribution.