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.

Despite staggering announcements for new AI data centers, a primary limiting factor will be the availability of electrical power. The current growth curve of the power infrastructure cannot support all the announced plans, creating a physical bottleneck that will likely lead to project failures and investment "carnage."

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.

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 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.

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.

Soaring power consumption from AI is widening the "power spread"—the difference between the cost to generate electricity and its selling price. This projected 15% expansion in profit margins will significantly boost earnings for power generation companies, creating massive value across the 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.

Most AI applications are designed to make white-collar work more productive or redundant (e.g., data collation). However, the most pressing labor shortages in advanced economies like the U.S. are in blue-collar fields like welding and electrical work, where current AI has little impact and is not being focused.