Authored by Michael Lebowitz via RealInvestmentAdvice.com,

The US economy’s curb appeal looks great. Consider that gasoline prices are nearly $5, crude oil is trading above $100, consumer sentiment is at historically low levels, and mortgage and other interest rates have remained relatively high. Yet, despite the worrisome headwinds, the US consumer-driven economy continues to expand. However, as with a house’s curb appeal, it’s not just the headline data that defines an economy. Equally important is its supporting structure. Let’s open the door to our economy to better appreciate how AI is currently impacting it and how it may change in the future.

The question we explore here is whether the AI investment boom is genuinely broadening this country’s economic footing or weakening the labor force, the foundation of the economy.

We separate the article into two parts. Part one is the optimistic case: an AI-induced, productivity-led economic boom in which the benefits spread quickly to society. Part Two will address a more bearish outlook: the possibility of a large gap in the distribution of AI’s productivity benefits, accruing to corporations much more quickly than to employees.

The amount of capital flowing into AI infrastructure development and thus GDP is enormous. As shown in the graph below, the capital expenditures (Capex) of just four companies, Amazon, Google, Microsoft, and Meta, are now over $700 billion annually, roughly 7x what they were five years ago.Based on the 2026 Capex expectations, a third of GDP growth could come from the four companies.

The AI buildout extends well beyond the four balance sheets noted above. Every dollar of Capex spent by the large hyperscalers creates demand across a wide supply chain. For example, construction firms are building data center campuses the size of small cities, utility companies are scrambling to add generation capacity, domestic semiconductor producers are ramping up output, and fiber optic and networking suppliers have multi-year order backlogs. The electrical grid is facing its first sustained demand growth in two decades, driven almost entirely by data center power requirements, which are projected to more than double by 2030.

The scale of today’s AI buildout has historical precedent. For instance, the railroad expansion of the mid-1800s involved more extreme infrastructure investment, with railway Capex estimated to have consumed as much as 10-20% of GDP at its peak. A more recent and appropriate comparison is the telecom buildout of the late 1990s, when Capex peaked at roughly 1.0-1.2% of US GDP. Today’s AI infrastructure spending by just the four companies has recently surpassed that telecom figure.

But unlike the debt-fueled telecom boom, today’s AI spending has thus far been funded almost entirely by the cash and cash flows of extremely profitable corporations. While the composition of funding is shifting from cash and free cash flow to debt, the companies noted above have debt-to-equity ratios well below the S&P 500 average and significantly lower than during the telecom buildout. Moreover, earnings from other highly profitable business lines will continue to provide them with substantial cash for investment.

While AI spending is tremendous and boosting the economy, some argue that it is masking weaknesses in consumer spending, which is the most important contributor to economic growth. The graph below shows that consumer spending accounts for about 67% of GDP, as it has since 2001. There has been no discernible change over the last few years since the advent of AI.

While the recent contribution of consumer spending has not changed meaningfully, its sustainability is a key factor driving future growth. While consumption is holding, there are signs that the means to spend are deteriorating. For instance, the personal savings rate has fallen to near its lowest level since 1960, as shown below. This suggests that a growing share of personal consumption is being funded by drawing down savings rather than by current earnings.

Source: ZeroHedge News