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.

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.

As a side hustle, lawyers are now working for data-labeling companies to train AI models on legal tasks. While they see it as being 'part of the change,' they are directly contributing to building the technology that could automate and devalue the very expertise they possess, potentially cannibalizing their future work.

As domain experts correct and verify AI output, they create high-quality training data. This data is then used to improve the AI, automating the very expertise the human provided. This forces experts into a continuous race to move up the value stack to stay relevant.

Companies like OpenAI and Anthropic are spending billions creating simulated enterprise apps (RL gyms) where human experts train AI models on complex tasks. This has created a new, rapidly growing "AI trainer" job category, but its ultimate purpose is to automate those same expert roles.

By replacing junior roles, AI eliminates the primary training ground for the next generation of experts. This creates a paradox: the very models that need expert data to improve are simultaneously destroying the mechanism that produces those experts, creating a future data bottleneck.

The "pyramid replacement" theory posits that AI will first make junior analyst and other entry-level positions obsolete. As AI becomes more agentic, it will climb the corporate ladder, systematically replacing roles from the base of the pyramid upwards.

Kara Swisher argues that AI will eliminate white-collar jobs like accounting and law before it replaces hands-on roles like nursing or plumbing. She urges professionals in digitized industries to proactively learn and integrate AI as a tool to augment their skills and avoid becoming obsolete.

Job seekers use AI to generate resumes en masse, forcing employers to use AI filters to manage the volume. This creates a vicious cycle where more AI is needed to beat the filters, resulting in a "low-hire, low-fire" equilibrium. While activity seems high, actual hiring has stalled, masking a significant economic disruption.