Contrary to a popular narrative, the surge in AI investment has not yet contributed measurably to US GDP growth. This is because the investment largely consists of imported goods, creating a neutral GDP effect, and accounting rules misclassify key semiconductor components as intermediate goods rather than final investment.
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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.
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.
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.
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.
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.
While AI investment has exploded, US productivity has barely risen. Valuations are priced as if a societal transformation is complete, yet 95% of GenAI pilots fail to positively impact company P&Ls. This gap between market expectation and real-world economic benefit creates systemic risk.
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.
The massive capex spending on AI data centers is less about clear ROI and more about propping up the economy. Similar to how China built empty cities to fuel its GDP, tech giants are building vast digital infrastructure. This creates a bubble that keeps economic indicators positive and aligns incentives, even if the underlying business case is unproven.