The initial job creation from AI isn't just for software engineers. It's driving a massive boom in physical infrastructure like data centers and chip fabs, creating high demand for skilled trades like electricians, plumbers, and construction workers.
Despite AI's narrative as a labor-replacement technology, NVIDIA's booming chip sales are occurring alongside strong job growth. This suggests that, for now, AI is acting as a productivity tool that is creating economic expansion and new roles faster than it is causing net job destruction.
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.
The insatiable demand for power from new data centers is so great that it's revitalizing America's dormant energy infrastructure. This has led to supply chain booms for turbines, creative solutions like using diesel truck engines for power, and even a doubling of wages for mobile electricians.
While AI is often viewed abstractly through software and models, its most significant current contribution to GDP growth is physical. The boom in data center construction—involving steel, power infrastructure, and labor—is a tangible economic driver that is often underestimated.
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.
Developed nations are building massive infrastructure projects like data centers, yet the construction workforce is aging and shrinking. This creates a critical bottleneck, as every project fundamentally relies on excavator operators—a role younger generations are avoiding.
AI is rapidly automating knowledge work, making white-collar jobs precarious. In contrast, physical trades requiring dexterity and on-site problem-solving (e.g., plumbing, painting) are much harder to automate. This will increase the value and demand for skilled blue-collar professionals.
The race to build AI data centers has created a severe labor shortage for specialized engineers. The demand is so high that companies are flying teams of engineers on private jets between construction sites, a practice typically reserved for C-suite executives, highlighting a critical bottleneck in the AI supply chain.
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.
The primary constraint on the AI boom is not chips or capital, but aging physical infrastructure. In Santa Clara, NVIDIA's hometown, fully constructed data centers are sitting empty for years simply because the local utility cannot supply enough electricity. This highlights how the pace of AI development is ultimately tethered to the physical world's limitations.