Beyond existential concerns, Wall Street analysts are highlighting a more immediate risk: AI-driven inflation. The massive, price-insensitive spending on data center construction is causing construction worker wages to spiral and increasing energy consumption, which could flow through to generalized inflation across the economy.

While the long-term productivity benefits of AI are uncertain, the short-term economic impact is clear. Building massive data centers requires immense physical resources like steel and energy, creating an immediate inflationary boom that contributes to an overheating economy in 2026.

Typically seen as a negative, Baumol's cost disease—where non-automatable sectors become relatively more expensive—becomes a feature in a post-AI world. The rising cost of human services stops being a budget problem and instead becomes a labor market solution, creating a virtuous cycle where employment grows precisely in sectors that resist automation.

The huge scale of AI data center construction, requiring thousands of skilled laborers in one location, creates a 'crowding out' effect. Local businesses in places like Abilene, Texas, cannot compete for labor like HVAC technicians, leading to shortages and potential inflationary pressures on regional economies.

Contrary to common belief, AI's initial impact is on white-collar roles like analysts and writers. The real bottleneck in the AI revolution is a shortage of skilled trades. Nvidia's CEO stated the biggest hurdle for data center construction is finding enough plumbers.

While AI may be deflationary in the long run, its immediate effect is inflationary. The immense capital expenditure on data centers, hardware, and energy strains supply chains, creates electricity shortages, and drives up prices for physical goods and skilled labor. Policymakers should focus on this immediate pressure, not on speculative future deflation.

AI will primarily threaten purely cognitive jobs, but roles combining thought with physical dexterity—like master electricians or plumbers—will thrive. The AI-driven infrastructure boom is increasing demand and pushing their salaries above even those of some Silicon Valley engineers.

The rapid expansion of AI data centers is constrained less by technology or capital and more by a critical shortage of skilled labor. An estimated 500,000 new jobs, particularly electricians needed for grid upgrades that require four years of training, are the most significant barrier to growth in the US.

Analyst Dylan Patel argues the biggest risk to the multi-trillion dollar AI infrastructure build-out is the lack of skilled blue-collar labor to construct and maintain data centers, as their wages are skyrocketing.