Credentials gap and automation: Does the replacement of jobs disproportionately impact workers in educationally mismatched occupations? - Liu, Larry (American Journal of STEM Education, 2026)
Credential gap refers to workers having more (overeducated) or less (undereducated) formal education than their occupations require. This study investigates whether prospective automation of occupations is related to the credential gap. Using quantitative Ordinary Least Squares (OLS) regressions and data from Gmyrek et al. (2023), Frey and Osborne (2017) and Burning Glass in 102 occupations, I find that computerization automation is associated with undereducated occupations, while there are no clear statistical effects for AI automation. These results suggest that traditional computerization may help ease skills shortages by reducing the need for extensive educational credentials, whereas AI-driven automation may not yet influence credential structures, highlighting policy and educational planning challenges in aligning college workforce training with evolving technological demands.