AI Is Killing the Career Ladder. A Stanford Economist Explains What Comes Next | Bharat Chandar

Stanford economist Bharat Chandar presents research findings showing young workers in AI-exposed jobs (software development, customer service, administrative roles) are experiencing 16% slower employment growth compared to peers in less AI-exposed fields. The study, using ADP payroll data tracking millions of US workers, finds experienced workers are largely unaffected so far. Chandar argues this is likely structural rather than temporary, as AI directly overlaps with the book-knowledge tasks entry-level workers typically perform. He identifies physical tasks, strategic thinking, and social interaction as areas where AI remains limited, and suggests future work will increasingly involve guiding AI agents rather than direct implementation. The optimistic scenario he envisions is a 'career lattice' enabled by AI-powered personalized learning, allowing workers to switch professions more easily as labor demand shifts, potentially reducing inequality if barriers to expertise fall.