The primary macroeconomic impact of AI in 2025 was not from supply-side productivity improvements but from demand-side wealth effects. A surge in AI-related stock values boosted the economy. The sustainability of this boost in 2026 depends on whether actual productivity gains materialize to justify high valuations.
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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.
The AI boom's economic impact extends beyond direct investment. With AI plays driving 80% of stock market gains, a powerful 'wealth effect' is created. This disproportionately benefits the top 10% of earners, who in turn drive the majority of US consumer spending, fueling the broader economy.
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.
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.
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.
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.
Even if AI drives productivity, it may not fuel broad economic growth. The benefits are expected to be narrowly distributed, boosting stock values for the wealthy rather than wages for the average worker. This wealth effect has diminishing returns and won't offset weaker spending from the middle class.
Just as electricity's impact was muted until factory floors were redesigned, AI's productivity gains will be modest if we only use it to replace old tools (e.g., as a better Google). Significant economic impact will only occur when companies fundamentally restructure their operations and workflows to leverage AI's unique capabilities.
