AI models will quickly automate the majority of expert work, but they will struggle with the final, most complex 25%. For a long time, human expertise will be essential for this 'last mile,' making it the ultimate bottleneck and source of economic value.

Contrary to the job loss narrative, AI will increase demand for knowledge workers. By drastically lowering the cost of their output (like code or medical scans), AI expands the number of use cases and total market demand, creating more jobs for humans to prompt, interpret, and validate the AI's work.

AI makes 'yesterday's expert competence' cheap, leading to an abundance of decent but generic outputs (e.g., code, essays). This devalues standard work and increases demand for true experts who can add nuance, create systems, or produce something genuinely novel that stands out.

As AI handles routine tasks like analysis and copywriting, the demand for uniquely human skills such as judgment, context, and strategic thinking grows. These crystallized intelligence skills, developed through decades of experience, make older workers more valuable, not less.

In fields like law and consulting, AI will automate the generation of work products (e.g., contract reviews). This commoditization will shift value upstream to uniquely human skills like providing strategic advice and experienced judgment based on the AI's output.

AI models are trained on past human work (code, articles, designs), making those skills cheap and accessible. This abundance creates homogenous, default outputs or "slop." Consequently, the market develops an urgent demand for human experts who can create something novel and differentiated, moving beyond the model's defaults.

Contrary to fears of devaluing expertise, AI makes deep experience more critical. Seasoned professionals can better prompt, guide, and spot flaws in AI output. This "context engineering" skill, honed over years, is essential for steering AI from generic results to high-quality, strategic outcomes.

The key economic risk from AI is not mass unemployment but the commodification of hard-won, specialized skills. This can reduce labor's overall value and its share of national income, shifting the focus from job quantity to the quality and value of work itself.

As AI handles more repetitive tasks, skills like critical judgment, communication, and domain expertise become more valuable, not less. The key competitive advantage is knowing how to use AI-generated output while recognizing its limitations and applying human oversight.