
AI Adoption and Labor Market Polarization: A Game-Theoretic Model Based on Occupational Substitution Elasticity
- 1 Zhejiang Gongshang University
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Abstract
This paper explores the dynamics of AI adoption and its impact on labor market polarization through a game-theoretic model incorporating occupational substitution elasticity. By modeling the strategic interaction between firms and heterogeneous labor groups, we demonstrate how differences in substitution elasticity between high-skill, middle-skill, and low-skill occupations lead to divergent outcomes in wage distribution, employment, and firm profitability. The results reveal that when the elasticity of substitution for middle-skill jobs is high, firms have stronger incentives to automate these roles, exacerbating labor market polarization. The findings provide a theoretical foundation to understand how technological advances—particularly in artificial intelligence—reshape labor structures, and suggest implications for education policy, labor regulation, and corporate strategy.
Keywords
AI adoption; labor market polarization; occupational substitution elasticity; game theory; automation; employment structure; wage inequality; technological unemployment
[1]. Acemoglu, D., & Autor, D. (2011). Skills, tasks and technologies: Implications for employment and earnings. Handbook of Labor Economics, 4, 1043–1171.
[2]. Acemoglu, D., & Restrepo, P. (2019). Automation and new tasks: How technology displaces and reinstates labor. Journal of Economic Perspectives, 33(2), 3–30.
[3]. Acemoglu, D., & Restrepo, P. (2020). Robots and jobs: Evidence from US labor markets. Journal of Political Economy, 128(6), 2188–2244.
[4]. Autor, D., Levy, F., & Murnane, R. (2003). The skill content of recent technological change. Quarterly Journal of Economics, 118(4), 1279–1333.
[5]. Autor, D., & Dorn, D. (2013). The growth of low-skill service jobs and the polarization of the US labor market. American Economic Review, 103(5), 1553–1597.
[6]. Benzell, S. G., Kotlikoff, L., LaGarda, G., & Sachs, J. (2015). Robots are us: Some economics of human replacement. NBER Working Paper No. 20941.
[7]. Brynjolfsson, E., & McAfee, A. (2014). The Second Machine Age. W. W. Norton.
[8]. Choudhury, P., Foroughi, C., & Larson, B. (2021). Work-from-anywhere: The productivity effects of geographic flexibility. Strategic Management Journal, 42(4), 655–683.
[9]. Frey, C., & Osborne, M. A. (2017). The future of employment: How susceptible are jobs to computerization? Technological Forecasting and Social Change, 114, 254–280.
[10]. Goos, M., Manning, A., & Salomons, A. (2014). Explaining job polarization. American Economic Review, 104(8), 2509–2526.
[11]. Graetz, G., & Michaels, G. (2018). Robots at work. Review of Economics and Statistics, 100(5), 753–768.
[12]. Hall, R. E., & Jones, C. I. (1999). Why do some countries produce so much more output per worker than others? Quarterly Journal of Economics, 114(1), 83–116.
[13]. Kaplan, J. (2015). Humans Need Not Apply: A Guide to Wealth and Work in the Age of Artificial Intelligence. Yale University Press.
[14]. Mokyr, J., Vickers, C., & Ziebarth, N. (2015). The history of technological anxiety and the future of economic growth. Journal of Economic Perspectives, 29(3), 31–50.
[15]. Nedelkoska, L., & Quintini, G. (2018). Automation, skills use and training. OECD Social, Employment and Migration Working Papers, No. 202.
[16]. Restrepo, P. (2022). The race between man and machine: Implications of technology for growth, factor shares, and employment. Review of Economic Dynamics, 44, 1–35.
[17]. Spence, M. (1977). Entry, capacity, investment and oligopolistic pricing. Bell Journal of Economics, 8(2), 534–544.
[18]. Vives, X. (1999). Oligopoly Pricing: Old Ideas and New Tools. MIT Press.
[19]. World Economic Forum. (2023). Future of Jobs Report.
[20]. Zilibotti, F. (2017). Growing and slowing down like China. Journal of the European Economic Association, 15(5), 943–988.
[21]. Zhang, L., & Zeng, Z. (2022). AI, labor substitution, and wage inequality: A task-based approach. China Economic Review, 72, 101733.
Cite this article
Li,C. (2025). AI Adoption and Labor Market Polarization: A Game-Theoretic Model Based on Occupational Substitution Elasticity. Journal of Economic and Managerial Dynamics,1(1),24-31.
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