Intelligence and the Future of Work: A Bibliometric Analysis of Job Displacement, Skills Transformation, and Workforce Adaptation

Artificial intelligence is reshaping work through automation, augmentation, algorithmic management, and new demands for skills, yet the literature remains dispersed across management, technology, education, economics, and labor studies. This study maps the development and conceptual structure of research on intelligence and the future of work, with particular attention to job displacement, skills transformation, and workforce adaptation. Bibliographic records were retrieved from Scopus using a structured query combining artificial intelligence, future-oriented terms, work and employment concepts, automation and digital transformation, and impact-related terms. Following the documented screening process, 432 publications covering 1994 to 2025 were analyzed using BiblioSpy®. The corpus recorded 13,550 citations, an annual growth rate of 17.57%, 1,255 unique authors, and an international co-authorship rate of 17.13%. Publication output accelerated sharply after 2019, reaching 151 documents in 2025. The United States led publication output and total citations, while the United Kingdom showed the highest average citation rate among the ten leading countries. Keyword co-occurrence mapping of 432 eligible records identified four connected clusters centered on artificial intelligence, automation, machine learning, and digital transformation. Together, these clusters show that the field links technological capability to changes in employment, human-AI collaboration, education, digital skills, productivity, ethics, and labor-market adjustment. The study provides an integrated map of the field, distinguishes productivity from influence, and identifies a research agenda that emphasizes longitudinal evidence, occupation-level transitions, inclusive reskilling, responsible deployment, and broader participation from underrepresented labor-market contexts. This synthesis offers a basis for comparing how technological change, labor-market institutions, and organizational responses shape workforce outcomes across contexts.

Artificial Intelligence

1. Acemoglu, D., & Restrepo, P. (2020). The wrong kind of AI? Artificial intelligence and the future of labour demand. Cambridge Journal of Regions, Economy and Society, 13(1), 25–35. [Google Scholar] [Crossref]

2. https://doi.org/10.1093/cjres/rsz022 [Google Scholar] [Crossref]

3. Agarwal, A. (2025). Optimizing employee roles in the era of generative AI: A multi-criteria decision-making analysis of co-creation dynamics. Cogent Social Sciences, 11(1), 2476737. [Google Scholar] [Crossref]

4. https://doi.org/10.1080/23311886.2025.2476737 [Google Scholar] [Crossref]

5. Bankins, S., & Formosa, P. (2023). The Ethical Implications of Artificial Intelligence (AI) For Meaningful Work. Journal of Business Ethics, 185(4), 725–740. https://doi.org/10.1007/s10551-023-05339-7 [Google Scholar] [Crossref]

6. Bughin, J. (2025). Corporate AI play and short term skill-biased AI change. Technology in Society, 82, 102904. https://doi.org/10.1016/j.techsoc.2025.102904 [Google Scholar] [Crossref]

7. C Conceição, L., F Pereira, L., & L Dias, Á. (2023). The Key Competencies for the Future of Work-A Bibliometric Study. Journal of Chinese Human Resource Management, 14(1), 3–37. [Google Scholar] [Crossref]

8. https://doi.org/10.47297/wspchrmWSP2040-800501.20231401 [Google Scholar] [Crossref]

9. Capello, R., Ciappei, S., & Lenzi, C. (2025). Digitalisation, platformisation and the transformations of local labour markets. Papers in Regional Science, 104(4), 100103. [Google Scholar] [Crossref]

10. https://doi.org/10.1016/j.pirs.2025.100103 [Google Scholar] [Crossref]

11. Chigbu, B. I., & Makapela, S. L. (2025). AI in education, sustainability, and the future of work: An integrative review of industry 5.0, education 5.0, and work 5.0. Journal of Open Innovation: Technology, Market, and Complexity, 11(4), 100645. https://doi.org/10.1016/j.joitmc.2025.100645 [Google Scholar] [Crossref]

12. Fouad, E. M. (2025). Predicting Jobs, Shaping Economies: Bibliometric Insights into AI and Big Data in Workforce Demand Analysis. International Journal of Advanced Computer Science and Applications, 16(6). [Google Scholar] [Crossref]

13. Jacob Fernandes França, T., São Mamede, H., Pereira Barroso, J. M., & Pereira Duarte Dos Santos, V. M. (2023). Artificial intelligence applied to potential assessment and talent identification in an organisational context. Heliyon, 9(4), e14694. https://doi.org/10.1016/j.heliyon.2023.e14694 [Google Scholar] [Crossref]

14. Jarrahi, M. H., Newlands, G., Lee, M. K., Wolf, C. T., Kinder, E., & Sutherland, W. (2021). Algorithmic management in a work context. Big Data & Society, 8(2), 20539517211020332. [Google Scholar] [Crossref]

15. https://doi.org/10.1177/20539517211020332 [Google Scholar] [Crossref]

16. Jetha, A., Liao, Q., Shahidi, F. V., Vu, V., Biswas, A., Smith, B., & Smith, P. (2025). Machine learning and the labor market: A portrait of occupational and worker inequities in Canada. Social Science & Medicine, 381, 118295. https://doi.org/10.1016/j.socscimed.2025.118295 [Google Scholar] [Crossref]

17. Katsamakas, E., Pavlov, O. V., & Saklad, R. (2024). Artificial Intelligence and the Transformation of Higher Education Institutions: A Systems Approach. Sustainability, 16(14), 6118. [Google Scholar] [Crossref]

18. https://doi.org/10.3390/su16146118 [Google Scholar] [Crossref]

19. Keith, M., Keiller, E., Windows-Yule, C., Kings, I., & Robbins, P. (2025). Harnessing generative AI in chemical engineering education: Implementation and evaluation of the large language model ChatGPT v3.5. Education for Chemical Engineers, 51, 20–33. https://doi.org/10.1016/j.ece.2025.01.002 [Google Scholar] [Crossref]

20. Khogali, H. O., & Mekid, S. (2023). The blended future of automation and AI: Examining some long-term societal and ethical impact features. Technology in Society, 73, 102232. [Google Scholar] [Crossref]

21. https://doi.org/10.1016/j.techsoc.2023.102232 [Google Scholar] [Crossref]

22. Kolbjørnsrud, V. (2024). Designing the Intelligent Organization: Six Principles for Human-AI Collaboration. California Management Review, 66(2), 44–64. [Google Scholar] [Crossref]

23. https://doi.org/10.1177/00081256231211020 [Google Scholar] [Crossref]

24. Krakowski, S. (2025). Human-AI agency in the age of generative AI. Information and Organization, 35(1), 100560. https://doi.org/10.1016/j.infoandorg.2025.100560 [Google Scholar] [Crossref]

25. Li, J. (Justin), Bonn, M. A., & Ye, B. H. (2019). Hotel employee’s artificial intelligence and robotics awareness and its impact on turnover intention: The moderating roles of perceived organizational support and competitive psychological climate. Tourism Management, 73, 172–181. [Google Scholar] [Crossref]

26. https://doi.org/10.1016/j.tourman.2019.02.006 [Google Scholar] [Crossref]

27. Lozie, D. R., Omasa, R., Hesami, S., Zaman, S., Kajbaf, M., & Malik, A. R. (2024). Examining the impact of generative artificial intelligence on work dynamics. Human Resources Management and Services, 6(2), 3420. https://doi.org/10.18282/hrms.v6i2.3420 [Google Scholar] [Crossref]

28. Morandini, S., Fraboni, F., De Angelis, M., Puzzo, G., Giusino, D., & Pietrantoni, L. (2023). The Impact of Artificial Intelligence on Workers’ Skills: Upskilling and Reskilling in Organisations. Informing Science: The International Journal of an Emerging Transdiscipline, 26, 039–068. https://doi.org/10.28945/5078 [Google Scholar] [Crossref]

29. Reeves Huapaya, E. S., Lazo Chucos, G., Parillo Sosa, E., & Meza, M. I. (2025). Disruptive technologies in the university curriculum: Use of artificial intelligence. International Journal of Evaluation and Research in Education (IJERE), 14(1), 671. https://doi.org/10.11591/ijere.v14i1.30450 [Google Scholar] [Crossref]

30. Rezapouraghdam, H., Ozturen, A., Haktanir, M., & Azinuddin, M. (2025). Examining the effects of industry transition to robotics, artificial intelligence, and service automation on hospitality and tourism students’ critical outcomes: Quitting or quiet quitting? Journal of Hospitality, Leisure, Sport & Tourism Education, 37, 100580. https://doi.org/10.1016/j.jhlste.2025.100580 [Google Scholar] [Crossref]

31. Stahl, B. C., Antoniou, J., Bhalla, N., Brooks, L., Jansen, P., Lindqvist, B., Kirichenko, A., Marchal, S., Rodrigues, R., Santiago, N., Warso, Z., & Wright, D. (2023). A systematic review of artificial intelligence impact assessments. Artificial Intelligence Review, 56(11), 12799–12831. [Google Scholar] [Crossref]

32. https://doi.org/10.1007/s10462-023-10420-8 [Google Scholar] [Crossref]

33. Tussyadiah, I. (2020). A review of research into automation in tourism: Launching the Annals of Tourism Research Curated Collection on Artificial Intelligence and Robotics in Tourism. Annals of Tourism Research, 81, 102883. https://doi.org/10.1016/j.annals.2020.102883 [Google Scholar] [Crossref]

34. Waelen, R. A. (2025). Rethinking Automation and the Future of Work with Hannah Arendt. Journal of Business Ethics, 201(1), 3–14. https://doi.org/10.1007/s10551-025-05991-1 [Google Scholar] [Crossref]

35. Wang, D., Weisz, J. D., Muller, M., Ram, P., Geyer, W., Dugan, C., Tausczik, Y., Samulowitz, H., & Gray, A. (2019). Human-AI Collaboration in Data Science: Exploring Data Scientists’ Perceptions of Automated AI. Proceedings of the ACM on Human-Computer Interaction, 3(CSCW), 1–24. https://doi.org/10.1145/3359313 [Google Scholar] [Crossref]

36. Wang, J., Kiran, E., Aurora, S. R., Simeone, M., & Lobo, J. (2025). ChatGPT on ChatGPT: An Exploratory Analysis of its Performance in the Public Sector Workplace. Digital Government: Research and Practice, 6(2), 1–28. https://doi.org/10.1145/3676281 [Google Scholar] [Crossref]

37. Yu, X., Xu, S., & Ashton, M. (2023). Antecedents and outcomes of artificial intelligence adoption and application in the workplace: The socio-technical system theory perspective. Information Technology & People, 36(1), 454–474. https://doi.org/10.1108/ITP-04-2021-0254 [Google Scholar] [Crossref]

38. Zhang, W., Lai, K.-H., & Gong, Q. (2024). The future of the labor force: Higher cognition and more skills. Humanities and Social Sciences Communications, 11(1), 479. https://doi.org/10.1057/s41599-024-02962-1 [Google Scholar] [Crossref]

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