Upskilling and lowered risks of AI-labor substitution: the impact of the National College Entrance Exam reform in China

Can education shield graduates from the storm of AI-induced displacement in the labor market? To address this research question, the study uses China’s National College Entrance Examination reform as a policy shock and examines how the abolition of the liberal arts–science tracking system affects graduates’ labor market outcomes. Following the upskilling framework and employing a cohort difference-in-differences research design, this study finds that graduates exposed to the National College Entrance Exam reform are more likely to secure an occupation with lower risks of AI-labor substitution, despite the reform not being designed to achieve this spillover effect. Further analyses reveal that this enhanced resilience stems from graduates sorting into occupations that demand higher levels of transferable abilities and work styles, competencies which remain less susceptible to AI-labor substitution. Operational skills are not one of the mediating skills because they are highly vulnerable to the displacement. The findings suggest that interdisciplinary training can endow students with skills irreplaceable in China’s AI-oriented labor market. Moreover, this benefit is more pronounced among students from high-income families than their counterparts from low-income families. Educational policies should be recalibrated to align with the context of rapid AI transformation.