Credentials gap and automation
Does the replacement of jobs disproportionately impact workers in educationally mismatched occupations?
DOI:
https://doi.org/10.32674/j0tzjm38Keywords:
Credentials gap, automation, AI, artificial intelligence, computerization, educational mismatch, overeducation, undereducationAbstract
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.
References
Acemoglu, D., & Restrepo, P. (2019). Automation and new tasks: How technology displaces and reinstates labor. Journal of Economic Perspectives, 33(2), 3-30. DOI: https://doi.org/10.1257/jep.33.2.3
Aghion, P., Antonin, C., Bunel, S., & Jaravel, X. (2021). The direct and indirect effects of automation on employment: A survey of the recent literature. Unpublished manuscript. DOI: https://doi.org/10.4324/9781003275534-2
Alpin, C., Shackleton, J. R., & Walsh, S. (1998). Over-and undereducation in the UK graduate labour market. Studies in Higher Education, 23(1), 17-34. DOI: https://doi.org/10.1080/03075079812331380462
Arntz, M., Gregory, T., & Zierahn, U. (2016). The risk of automation for jobs in OECD countries: A comparative analysis. OECD Working Paper, No.189.
Arranz, J., & García‐Serrano, C. (2025). Has it gone down the drain? The influence of overeducation on the wages of young workers. International Journal of Manpower. https://doi.org/10.1108/ijm-03-2024-0200. DOI: https://doi.org/10.1108/IJM-03-2024-0200
Bessen, J. (2019). Automation and jobs: When technology boosts employment. Economic Policy, 34(100), 589-626. DOI: https://doi.org/10.1093/epolic/eiaa001
Bessen, J., Denk, E., & Meng, C. (2022). The remainder effect: How automation complements labor quality. Boston University School of Law Research Paper Series, (22-3). DOI: https://doi.org/10.2139/ssrn.4042317
Borgna, C., Solga, H., & Protsch, P. (2019). Overeducation, labour market dynamics, and economic downturn in Europe. European Sociological Review, 35(1), 116-132. DOI: https://doi.org/10.1093/esr/jcy046
Braverman, H. (1974). Labor and Monopoly Capital. Monthly Review Press. DOI: https://doi.org/10.14452/MR-026-03-1974-07_1
Burning Glass. (2014). Moving the goalposts: How demand for a bachelor’s degree is reshaping the workforce.
Cappelli, P. H. (2015). Skill gaps, skill shortages, and skill mismatches: Evidence and arguments for the United States. ILR review, 68(2), 251-290. DOI: https://doi.org/10.1177/0019793914564961
Casilli, A. A. (2025). Waiting for robots: The hired hands of automation. University of Chicago Press.
Chen, L., & Hu, J. (2023). Overeducation and Social Integration Among Highly Educated Migrant Workers in China. Social Indicators Research, 170, 25 - 49. https://doi.org/10.1007/s11205-023-03145-2. DOI: https://doi.org/10.1007/s11205-023-03145-2
Collins, R. (1979). The credential society: An historical sociology of education and stratification. Academic Press.
Downey, M. (2021). Partial automation and the technology-enabled deskilling of routine jobs. Labour Economics, 69, 101973. DOI: https://doi.org/10.1016/j.labeco.2021.101973
Ellingrud, K., Sanghvi S., Dandona G.S., Madgavkar, A., Chui, M., White, O, & Hasebe, P. (2023). Generative AI and the future of work in America. McKinsey. https://www.mckinsey.com/mgi/our-research/generative-ai-and-the-future-of-work-in-america
Frank, R. H. (1978). Why women earn less: The theory and estimation of differential overqualification. The American Economic Review, 68(3), 360-373.
Frey, C. B., & Osborne, M. A. (2017). The future of employment: How susceptible are jobs to computerisation?. Technological forecasting and social change, 114, 254-280. DOI: https://doi.org/10.1016/j.techfore.2016.08.019
Ghodsi, M., Tverdostup, M., & de Lange, T. (2025). Migration or automation? Recommendations for how to better navigate labour shortages in the EU. The Vienna Institute for International Economic Studies. https://wiiw.ac.at/migration-or-automation-recommendations-for-how-to-better-navigate-labour-shortages-in-the-eu-dlp-7283.pdf
Gmyrek, P., Berg, J., & Bescond, D. (2023). Generative AI and jobs: A global analysis of potential effects on job quantity and quality. ILO Working Paper 96. https://webapps.ilo.org/static/english/intserv/working-papers/wp096/index.html DOI: https://doi.org/10.54394/FHEM8239
Goldin, C. D., & Katz, L. F. (2008). The race between education and technology. Harvard University Press.
Graetz, G., & Michaels, G. (2018). Robots at work. Review of Economics and Statistics, 100(5), 753-768. DOI: https://doi.org/10.1162/rest_a_00754
Horbach, J., & Rammer, C. (2022). Skills shortage and innovation. Industry and Innovation, 29(6), 734-759. DOI: https://doi.org/10.1080/13662716.2021.1990021
Khan, A., Shad, F., Sethi, S., & Bibi, M. (2024). The impact of Artificial Intelligence (AI) on job displacement and the future work. Social Science Review Archives, 2(2), 2296-2306. DOI: https://doi.org/10.70670/sra.v3i1.509
Livingstone, D. W. (2019). Underemployment of highly qualified labour in advanced capitalism: Trends and prospects. Journal of Education and Work, 32(4), 305-319. DOI: https://doi.org/10.1080/13639080.2019.1646415
Macnamara, B., Berber, I., Çavusoglu, M., Krupinski, E., Nallapareddy, N., Nelson, N., Smith, P., Wilson-Delfosse, A., & Ray, S. (2024). Does using artificial intelligence assistance accelerate skill decay and hinder skill development without performers’ awareness?. Cognitive Research: Principles and Implications, 9. https://doi.org/10.1186/s41235-024-00572-8. DOI: https://doi.org/10.1186/s41235-024-00572-8
Madoń, K. (2024). The relationship between Artificial Intelligence (AI) exposure and returns to education. Central European Economic Journal, 11(58), 461-474. DOI: https://doi.org/10.2478/ceej-2024-0029
Marioni, L. D. S. (2021). Overeducation in the labour market: evidence from Brazil. Education Economics, 29(1), 53-72. DOI: https://doi.org/10.1080/09645292.2020.1832201
McGuinness, S. (2006). Overeducation in the labour market. Journal of Economic Surveys, 20(3), 387-418. DOI: https://doi.org/10.1111/j.0950-0804.2006.00284.x
Rawashdeh, A. (2025). The consequences of artificial intelligence: an investigation into the impact of AI on job displacement in accounting. Journal of Science and Technology Policy Management, 16(3), 506-535. DOI: https://doi.org/10.1108/JSTPM-02-2023-0030
Schmelzer, P., & Schneider, T. (2020). Consequences of overeducation among career starters in Germany: A trap for the vocationally trained as well as for university graduates?. European Sociological Review, 36, 413-428. https://doi.org/10.1093/esr/jcz061. DOI: https://doi.org/10.1093/esr/jcz061
Schumpeter, J. A. (2013 [1942]). Capitalism, socialism and democracy. Routledge. DOI: https://doi.org/10.4324/9780203202050
Shestakofsky, B. (2017). Working algorithms: Software automation and the future of work. Work and Occupations, 44(4), 376-423. DOI: https://doi.org/10.1177/0730888417726119
Smith, G. (2018). The intelligent solution: automation, the skills shortage and cyber-security. Computer Fraud & Security, 2018(8), 6-9. DOI: https://doi.org/10.1016/S1361-3723(18)30073-3
Summerfield, F. (2021). Economic conditions, task shares, and overqualification. Oxford Economic Papers. https://doi.org/10.1093/oep/gpab002. DOI: https://doi.org/10.1093/oep/gpab002
Tijdens, K. G., & van Klaveren, M. (2011). Over-and underqualification of migrant workers. Evidence from Wage Indicator survey data. Amsterdam, University of Amsterdam, AIAS Working Paper, 11, 110.
Tubaro, P. (2019). Décrypter la société des plateformes : Organisations, marchés et réseaux dans l’économie numérique. Sociology. Institut d’Etudes Politiques de Paris. https://hal.science/tel-04547405/document
Vaisey, S. (2006). Education and its Discontents: Overqualification in America, 1972-2002. Social Forces, 85, 835 - 864. https://doi.org/10.1353/sof.2007.0028. DOI: https://doi.org/10.1353/sof.2007.0028
Xue, M., Cao, X., Feng, X., Gu, B., & Zhang, Y. (2022). Is college education less necessary with AI? Evidence from firm-level labor structure changes. Journal of Management Information Systems, 39(3), 865-905. DOI: https://doi.org/10.1080/07421222.2022.2096542
Yamada, G. (2015). The boom in university graduates and the risk of underemployment. IZA World of Labor. DOI: https://doi.org/10.15185/izawol.165
Additional Files
Published
Issue
Section
License
Copyright (c) 2026 Larry Liu
This work is licensed under a Creative Commons Attribution 4.0 International License.
Copyright (c) [year] [author]
This work is licensed under a Creative Commons Attribution 4.0 International License.
This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. https://creativecommons.org/licenses/by/4.0
Call for Special Issue Proposals 
