The labor market is a single interconnected system. As AI eliminates white-collar roles, displaced professionals will flood the blue-collar and gig economies, increasing labor supply and creating downward wage pressure across all sectors.

AI cannot solve 'Baumol's disease'—the stagnant productivity in labor-intensive services like plumbing and electrical work. In fact, the AI build-out worsens it by consuming scarce skilled labor for data center construction and maintenance, driving up costs for these essential services for the rest of the economy.

Unlike cyclical downturns where jobs eventually return, AI is permanently replacing cognitive roles. The selective targeting of the knowledge economy while manual labor remains stable indicates a structural shift, not a temporary economic dip. These white-collar jobs are not coming back.

Instead of outright replacing entire roles, AI is more likely to cause significant wage compression. As AI makes certain skills more common, it floods the labor supply for those tasks, driving down pay for both displaced workers and incumbents in affected fields.

Despite a 52-year explosion in technology and worker productivity, the average American worker's real weekly wages, adjusted for inflation, are lower today than in 1973. This highlights a fundamental failure of the economic system to distribute gains from innovation to labor.

AI is beginning to impact labor not by firing employees, but by reducing the need for new hires, particularly in white-collar roles like consulting and business services. This will likely suppress wage growth at the higher end, creating a natural rebalancing of the K-shaped economy from the top down.

Previous technological shifts primarily automated low-skill jobs, widening inequality. AI, however, is poised to replace or augment tasks done by high-earning knowledge workers. This could lead to a compression of the wage distribution, a reversal of historical trends driven by technology.

The idea that AI will create net new jobs is challenged by the Jevons paradox. Even if demand for work increases, AI's ability to increase the supply of that work even faster leads to wage compression for humans, as seen with London cab drivers post-GPS/Uber.

Capitalism values scarcity. AI's core disruption is not just automating tasks, but making human-like intellectual labor so abundant that its market value approaches zero. This breaks the fundamental economic loop of trading scarce labor for wages.