Despite pessimistic CBO reports, strong GDP growth, massive AI-related Capex ($600B from just four hyperscalers), and robust private sector job creation signal an economic boom. This period may be looked back upon as a new 'golden age' masked by political noise, similar to the late 1990s.
Related Insights
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.
Elon Musk theorizes that if 'applied intelligence' is a direct proxy for economic growth, the exponential advancement of AI could lead to unprecedented double-digit GDP growth within 18 months and potentially triple-digit growth in five years. This frames AI not just as a tool, but as the primary driver of a new economic golden era.
The current AI-driven CapEx cycle is analogous to historical bubbles like the 19th-century railroad buildout and the dot-com boom. These periods of intense capital investment have historically led to major economic downturns and secular bear markets, suggesting a grim multi-year outlook beyond the current cycle.
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.
The long-term health of U.S. fiscal policy appears heavily dependent on a future surge in corporate capital expenditures. This spending is expected to fuel a growth burst specifically in the manufacturing and AI sectors, driven by the strategic imperative to outcompete China.
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.
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.
The US economy is seeing a rare combination of high government deficits, massive AI-driven corporate investment, and bank deregulation. If the Federal Reserve also cuts rates based on labor market fears, this confluence of fiscal, corporate, and monetary stimulus could ignite unprecedented corporate risk-taking if growth holds up.