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.

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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.

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.

The AI industry and the US government both require trillions in funding. This creates a paradox: the more successful AI becomes, the more it erodes the white-collar tax base by automating jobs, forcing the Treasury to borrow even more and intensifying the competition for scarce capital.

The world's most profitable companies view AI as the most critical technology of the next decade. This strategic belief fuels their willingness to sustain massive investments and stick with them, even when the ultimate return on that spending is highly uncertain. This conviction provides a durable floor for the AI capital expenditure 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 global shift away from centralized manufacturing (deglobalization) requires redundant investment in infrastructure like semiconductor fabs in multiple countries. Simultaneously, the AI revolution demands enormous capital for data centers and chips. This dual surge in investment demand is a powerful structural force pushing the neutral rate of interest higher.

Geopolitical competition with China has forced the U.S. government to treat AI development as a national security priority, similar to the Manhattan Project. This means the massive AI CapEx buildout will be implicitly backstopped to prevent an economic downturn, effectively turning the sector into a regulated utility.

The massive capital expenditure on AI infrastructure is not just a private sector trend; it's framed as an existential national security race against China's superior electricity generation capacity. This government backing makes it difficult to bet against and suggests the spending cycle is still in its early stages.

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 economy's apparent strength is misleadingly concentrated. Growth hinges on AI-related capital expenditures and spending by the top 20% of households. This narrow base makes the economy fragile and vulnerable to a single shock in these specific areas, as there is little diversity to absorb a downturn.