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The Impact of Artificial Intelligence on Employment: A Panel Data Analysis for Selected Countries

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  • Cemre Nur ÇETİN
  • Erol KUTLU

Abstract

Various artificial intelligence technologies such as robotics, machine learning, natural language processing, deep learning, and automation have developed rapidly in recent years and their use has become increasingly widespread in all areas that can affect the economy. These technologies have the capacity to optimize production processes, enhance efficiency levels, and play a decisive role in shaping trade and economic growth. Furthermore, they possess significant potential to exert notable impacts on employment and income inequality. The rise of artificial intelligence has sparked widespread debate, particularly regarding its potential impact on employment dynamics. The study analyzes the effect of artificial intelligence on employment in 29 countries from 2017 to 2021 using the System-GMM estimator. The results showed a statistically significant positive effect of artificial intelligence on employment. The analysis also considers the potential impact of labor productivity on employment in relation to artificial intelligence technologies by including an interaction term in the same model. The estimation results show that while the impact of artificial intelligence and labor productivity on employment is positive when considered individually, the interaction term diminishes this positive effect.

Suggested Citation

  • Cemre Nur ÇETİN & Erol KUTLU, 2025. "The Impact of Artificial Intelligence on Employment: A Panel Data Analysis for Selected Countries," Journal of Research in Economics, Politics & Finance, Ersan ERSOY, vol. 10(1), pages 202-233.
    • Handle: RePEc:ahs:journl:v:10:y:2025:i:1:p:202-233
    DOI: https://doi.org/10.30784/epfad.1621455
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    References listed on IDEAS

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    3. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
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    Keywords

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    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • J23 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Demand
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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