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.

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Morgan Stanley frames AI-related capital expenditure as one of the largest investment waves ever recorded. This is not just a sector trend but a primary economic driver, projected to be larger than the shale boom of the 2010s and the telecommunications spending of the late 1990s.

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.

Within just six months, AI-related investment has transformed from a niche topic to a primary focus in top-down cyclical discussions at major global finance conferences like the IMF/World Bank meetings. This rapid shift highlights its perceived impact on global growth and employment.

For 2026, massive capital expenditure on AI infrastructure like data centers and semiconductors will fuel economic demand and inflation. The widely expected productivity gains that lower inflation are a supply-side effect that will take several years to materialize.

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.

While AI is often viewed abstractly through software and models, its most significant current contribution to GDP growth is physical. The boom in data center construction—involving steel, power infrastructure, and labor—is a tangible economic driver that is often underestimated.

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.

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.

Unlike prior technological inputs like energy, which required machinery to be useful, AI compute can be added directly to the economy to strengthen it. Simply increasing compute improves product quality and expands user access simultaneously, acting as a direct economic force multiplier without traditional bottlenecks.

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.