AI Is Killing the Career Ladder. A Stanford Economist Explains What Comes Next | Bharat Chandar
In a Nutshell
AI is causing 16% slower employment growth for young workers in exposed jobs like software development and customer service, acting as "canaries in the coal mine" for structural labor market shifts, while experienced workers with tacit knowledge remain resilient. Firms under-invest in training youth due to mobility risks, but AI as a personalized learning tool can accelerate skill acquisition in strategic thinking and social skills, enabling a flexible "career lattice" over rigid ladders. Young people should build extensively with AI, focus on human strengths like values and guidance, and embrace profession-switching to thrive amid rapid AI advances.
These notes were generated by AI and may contain inaccuracies.
Jobs more exposed to AI show young workers experiencing 16% slower employment growth, a significant effect. Structural changes from AI capabilities impacting the labor market are not temporary. Unlocking AI for helping people learn could make switching professions easier, leading to a career lattice that benefits workers over a rigid career ladder with higher risk from technological change.
Barat Chandra (corrected from Barat Chandra), economist at the Stanford Digital Economy Lab, studies AI's impact on work. Over the past year and a half, AI's labor market effects became a central question in labor economics. Using AI tools shifted his research agenda due to their societal importance.
Released study with collaborators Eric Bolson and Ryu Chen using ADP payroll data tracking millions of US workers. Compared jobs more vs. less exposed to AI. Overall, no major employment differences. For young workers, divergence: AI-exposed jobs (e.g., software development, customer service, administrative roles) show employment declines; less-exposed jobs continue growth. Experienced workers see on-trend growth. Young workers in AI-exposed jobs have 16% slower employment growth.
Title reflects young workers as early indicators of AI's transformative impacts. Uncertain if driven by AI or temporary; tested alternatives like interest rates (AI-exposed jobs less affected, e.g., transportation, construction more interest-rate sensitive), tech overhiring (results hold excluding tech/computer jobs). If structural AI change, it's long-run. Need ongoing tracking; no clean AI vs. no-AI experiment, more research needed.
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