The Impact of Artificial Intelligence–Driven Recruitment on Employee Performance and Retention

Authors

  • Vaibhavi Ghat Assistant Professor, Dr. Ambedkar Institute of Management Studies and Research, Nagpur Author
  • Atharva Desai Assistant Branch Manager, DNS Bank, Nagpur Author

DOI:

https://doi.org/10.31305/rrijm.2026.CI.v11.n06.007

Keywords:

Artificial Intelligence, Recruitment, selection, employee performance

Abstract

Identification, attraction, and selection of candidates for employment inside an organization is known as recruitment. This process entails a strategic approach that is in line with the organization's objectives and culture; it is not only about filling positions. AI is often linked to efficiency and automation, its real potential in change management is in addressing the human aspect of transition. The stakes are bigger than ever for HR directors, talent acquisition managers, and people operations teams as the workplace rapidly changes. The goal of the current study is to shed light on how businesses might use artificial intelligence in hiring and selection to promote long-term employee retention, improve employee performance, and make better hiring decision. For the purpose of the study, a self-designed questionnaire was developed and distributed among employees working across different sectors and professions to collect relevant primary data. Correlation was used in the study shows that there is a direct relationship between employee performance and retention levels and use of AI in hiring process.

References

[1] Alston, A. J., Roberts, R., & English, C. W. (2019). Building a Sustainable Agricultural Career Pipeline: Effective Recruitment and Retention Practices Used by Colleges of Agriculture in the United States. Journal of Research in Technical Careers, 3(2), 1-23. DOI: https://doi.org/10.9741/2578-2118.1073

[2] Alvesson, M., & Sveningsson, S. (2024). Changing organizational culture: Cultural change work in progress. Routledge. DOI: https://doi.org/10.4324/9781003474555

[3] Basnet, S. (2024). The impact of AI-driven predictive analytics on employee retention strategies. International Journal of Research and Review, 11(9), 50-65. DOI: https://doi.org/10.52403/ijrr.20240906

[4] Breaugh, J. A. (2017). The contribution of job analysis to recruitment. The Wiley Blackwell handbook of the psychology of recruitment, selection and employee retention, 12-28. DOI: https://doi.org/10.1002/9781118972472.ch2

[5] Djabatey, E.N. 2012. Recruitment and selection practices of organisation. A case study of HFC bank (GH) Ltd.

[6] Kadirov, A., Shakirova, Y., Ismoilova, G., & Makhmudova, N. (2024, April). AI in human resource management: reimagining talent acquisition, development, and retention. In 2024 International Conference on Knowledge Engineering and Communication Systems (ICKECS) (Vol. 1, pp. 1-8). IEEE. DOI: https://doi.org/10.1109/ICKECS61492.2024.10617231

[7] Kayrouz, R., Dear, B. F., Karin, E., & Titov, N. (2016). Facebook as an effective recruitment strategy for mental health research of hard to reach populations. Internet interventions, 4, 1-10. DOI: https://doi.org/10.1016/j.invent.2016.01.001

[8] Mohebianfar, E. (2025). An AI-driven approach to improve talent retention and mobility.

[9] Őnday, Ő. (2016). Classical to modern organization theory. Journal of Advance Management and Accounting Research, 3(9), 13-59.

[10] Rehman, H. U., Shahani, A. K., & Waheed, H. (2025). Artificial Intelligence in HR: Revolutionizing Talent Acquisition and Employee Retention. International Journal of Social Sciences Bulletin, 3(4), 420-431.

[11] Saviour, A. W., Kofi, A., Yao, B. D., & Kafui, L. A. (2016). The impact of effective recruitment and selection practice on organisational performance (a case study at University of Ghana). Global journal of management and business research, 16(11), 25-34.

[12] Walker, James. 2009. Human Resource Planning. New York: McGraw-Hill Book Co., P95.

Published

2026-06-15

How to Cite

Ghat, V., & Desai, A. (2026). The Impact of Artificial Intelligence–Driven Recruitment on Employee Performance and Retention. RESEARCH REVIEW International Journal of Multidisciplinary, 11(6), 38-43. https://doi.org/10.31305/rrijm.2026.CI.v11.n06.007