Artificial Intelligence and Employee Performance: A Human Resource Management Perspective

Authors

  • Mehak Maqbool Masters in Accounting & Finance, Bahauddin Zakariya University, Multan, Pakistan
  • Komal Batool Masters in Management Science, National College of Business Administration & Economics, Pakistan
  • Usama Javed MBA, Institute of Business, Management and Administrative Sciences, The Islamia University, Bahawalpur, MPhil Anthropology, Institute of Social and Cultural Studies. Bahauddin Zakariya University, Multan, Pakistan
  • Zahra Syed MPhil Education, University of Education, Pakistan
  • Iqra Abbas Masters in Human Resource Management, Virtual University, Faisalabad, Pakistan

DOI:

https://doi.org/10.63544/jbii.v5i9.208

Keywords:

Artificial Intelligence, Human Resource Management, Employee Performance, AI in HRM, Employee Feedback

Abstract

Artificial Intelligence (AI) is transforming Human Resource Management (HRM) practices, offering opportunities to enhance employee performance through data-driven decision-making, automated feedback, and streamlined HR processes. This article examines the impact of AI on employee performance from an HRM perspective, drawing on a literature-based research method that synthesizes findings from recent academic studies. The review focuses on three key areas: AI-based HRM practices, employee performance and productivity, and the challenges of AI adoption. The review analyses AI applications in recruitment, performance evaluation, training and development, and workforce decision-making, while also addressing the ethical and organizational challenges associated with AI adoption. The findings indicate that AI can significantly improve employee productivity, motivation, and job performance when integrated effectively into HRM practices. Specifically, AI-enabled performance feedback, particularly when constructive and learning-oriented, enhances employee development and reduces interpersonal concerns. However, the review also identifies critical challenges, including algorithmic bias, privacy and data security risks, lack of transparency, and employee resistance. These factors can undermine the effectiveness and fairness of AI-based HR decisions. The study emphasizes that AI should augment rather than replace human judgment, with human oversight remaining essential for ethical and equitable outcomes. Organizational support, employee training, clear policies, and trust-building are identified as key conditions for successful AI implementation. Overall, the evidence suggests that AI has substantial potential to enhance HRM and employee performance, but its benefits depend on responsible adoption, transparency, and the preservation of human control in decision-making processes. The article concludes that a balanced integration of AI and human expertise is crucial for maximizing employee performance and maintaining fairness in contemporary organizations.

Agustono, D. O. S., Nugroho, R., & Fianto, A. Y. A. (2023). Artificial intelligence in human resource management practices. KnE Social Sciences, 8(9), 958–970. https://doi.org/10.18502/kss.v8i9.13409

Alsaif, A., & Sabih Aksoy, M. (2023). AI-HRM: Artificial intelligence in human resource management: A literature review. Journal of Computing and Communication, 2(2), 1–7.

Bujold, A., Roberge-Maltais, I., Parent-Rocheleau, X., Boasen, J., Sénécal, S., & Léger, P.-M. (2024). Responsible artificial intelligence in human resources management: A review of the empirical literature. AI and Ethics, 4(4), 1185–1200. https://doi.org/10.1007/s43681-023-00325-1

Budhwar, P., Chowdhury, S., Wood, G., Aguinis, H., Bamber, G. J., Beltran, J. R., Boselie, P., Cooke, F. L., Decker, S., DeNisi, A., Dey, P. K., Guest, D., Knoblich, A. J., Malik, A., Paauwe, J., Papagiannidis, S., Patel, C., Pereira, V., Ren, S., … Varma, A. (2023). Human resource management in the age of generative artificial intelligence: Perspectives and research directions on ChatGPT. Human Resource Management Journal, 33(3), 606–659. https://doi.org/10.1111/1748-8583.12524

Halid, H., Ravesangar, K., Mahadzir, S. L., & Halim, S. N. A. (2024). Artificial intelligence (AI) in human resource management (HRM). In Building the future with human resource management (pp. 37–70). Springer International Publishing. https://doi.org/10.1007/978-3-031-52811-8_2

Irvan, M., Syahroni, B., & Mahadianto, M. Y. (2026). Transparency, algorithmic fairness, and employee performance in AI-based HR: The moderating role of trust in management. Indonesian Journal Economic Review, 6(1), 101–115. https://doi.org/10.59431/ijer.v6i1.729

Jia, Q., Guo, Y., Li, R., Li, Y., & Chen, Y. (2018). A conceptual artificial intelligence application framework in human resource management. In 2018 International Conference on Electronic Business (ICEB 2018) (Paper 91). AIS eLibrary.

Kadirov, A., Shakirova, Y., Ismoilova, G., & Makhmudova, N. (2024). 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. https://doi.org/10.1109/ICKECS61492.2024.10617231

Keong, L. M., Vui, C. H. N., & Ling, L. S. (2025). Artificial intelligence AI-powered employee performance evaluation. International Journal of Research and Innovation in Social Science, 9(2), 1352–1365. https://doi.org/10.47772/IJRISS.2025.9020109

Madhumita, G., Diana, P. D., P. C., N., Kiran, P. N., Aggarwal, S., & Nargunde, A. S. (2024). AI-powered performance management: Driving employee success and organizational growth. In 2024 5th International Conference on Recent Trends in Computer Science and Technology (ICRTCST) (pp. 204–209). IEEE. https://doi.org/10.1109/ICRTCST61793.2024.10578371

Mohamed, H. H., Matimbwa, H., & Banzi, J. (2025). Unveiling the potential of artificial intelligence in human resource management: A systematic review of adoption strategies, challenges, and future directions. Cureus Journal of Business and Economics, 2, Article es44404-025-03698-0. https://doi.org/10.7759/s44404-025-03698-0

Pan, Y., Froese, F. J., & Xue, S. (2026). The role of AI in performance appraisal: A mixed-method study of employee experience through a relational lens. Human Resource Management, 65(3), 781–798. https://doi.org/10.1002/hrm.70049

Pei, J., Wang, H., Peng, Q., & Liu, S. (2024). Saving face: Leveraging artificial intelligence-based negative feedback to enhance employee job performance. Human Resource Management, 63(5), 775–790. https://doi.org/10.1002/hrm.22226

Prasad, K. D. V., & De, T. (2024). Generative AI as a catalyst for HRM practices: Mediating effects of trust. Humanities and Social Sciences Communications, 11, Article 1362. https://doi.org/10.1057/s41599-024-03842-4

Seth, M., Sharma, S., Belwal, R., Mahmood, A., Jha, A., & Kumar, V. (2026). High-performance HR techniques in the artificial intelligence era: Encouraging employee achievement. Strategic Business Research, 2(1), Article 100216. https://doi.org/10.1016/j.sbr.2026.100216

Shaikh, F., Afshan, G., Anwar, R. S., Abbas, Z., & Chana, K. A. (2023). Analyzing the impact of artificial intelligence on employee productivity: The mediating effect of knowledge sharing and well-being. Asia Pacific Journal of Human Resources, 61(4), 794–820. https://doi.org/10.1111/1744-7941.12385

Shahzad, M. F., Xu, S., Naveed, W., & Nusrat, S. (2023). Investigating the impact of artificial intelligence on human resource functions in the health sector of China: A mediated moderation model. Heliyon, 9(11), Article e21818. https://doi.org/10.1016/j.heliyon.2023.e21818

Tambe, P., Cappelli, P., & Yakubovich, V. (2019). Artificial intelligence in human resources management: Challenges and a path forward. California Management Review, 61(4), 15–42. https://doi.org/10.1177/0008125619867910

Ullah, M., Din, M. U., Khan, F., & Mushtaq, S. (2025). Artificial intelligence in human resource management: A case of information technology sector of Khyber Pakhtunkhwa, Pakistan. Journal of Political Stability Archive, 3(1), 1099–1117. https://doi.org/10.63468/jpsa.3.1.6

Umer, W., Furnaz, R., Sadiq, B., Bashir, T., & Naseem, A. (2024). Study on the impact of AI-powered GHRM practices on employee behavior and organizational performance: Evidence from SMEs of Pakistan. In 2024 International Conference on Horizons of Information Technology and Engineering (HITE). IEEE. https://doi.org/10.1109/HITE63532.2024.10777190

Votto, A. M., Valecha, R., Najafirad, P., & Rao, H. R. (2021). Artificial intelligence in tactical human resource management: A systematic literature review. International Journal of Information Management Data Insights, 1(2), Article 100047. https://doi.org/10.1016/j.jjimei.2021.100047

Wagan, S. M., & Sidra, S. (2025). Artificial intelligence in human resource management: A systematic review of adoption, impact, and challenges. AYBU Business Journal, 5(2), 1–19. https://doi.org/10.61725/abj.1786837

Zahoor, S., Chaudhry, I. S., Yang, S., … Ren, X. (2025). Artificial intelligence application and high-performance work systems in the manufacturing sector: A moderated-mediating model. Artificial Intelligence Review, 58, Article 11. https://doi.org/10.1007/s10462-024-11013-9

Zhu, Y. (2024). Research on the influence of artificial intelligence technology in enterprise human resource management on employee performance. Frontiers in Business, Economics and Management, 15(3), 116–119. https://doi.org/10.54097/gghb5k57

Author Biographies

Mehak Maqbool, Masters in Accounting & Finance, Bahauddin Zakariya University, Multan, Pakistan

Komal Batool, Masters in Management Science, National College of Business Administration & Economics, Pakistan

Usama Javed, MBA, Institute of Business, Management and Administrative Sciences, The Islamia University, Bahawalpur, MPhil Anthropology, Institute of Social and Cultural Studies. Bahauddin Zakariya University, Multan, Pakistan

Zahra Syed, MPhil Education, University of Education, Pakistan

Iqra Abbas, Masters in Human Resource Management, Virtual University, Faisalabad, Pakistan

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Published

2026-09-12

How to Cite

Maqbool, M., Batool, K., Javed, U., Syed, Z., & Abbas, I. (2026). Artificial Intelligence and Employee Performance: A Human Resource Management Perspective. Journal of Business Insight and Innovation, 5(9), 162–172. https://doi.org/10.63544/jbii.v5i9.208

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