Impact of Artificial Intelligence on Human Resource Management Practices: A Qualitative Study in Hyderabad, Pakistan’s Banking Sector
DOI:
https://doi.org/10.29145/jmr.121.04Keywords:
artificial intelligence, human resource management, performance management, recruitment efficiencyAbstract
Artificial Intelligence (AI) is reshaping the way Human Resource Management (HRM) functions within organizations. The core areas, such as performance evaluation, employee motivation, retention strategies, and ethical practices are highly influenced by AI. Simultaneously, its use raises new concerns, for instance, data privacy. The current study adopted a qualitative approach to explore how AI is impacting HRM practices and how it can be applied effectively in real-world settings. A total of 15 semi-structured interviews were conducted with Human Resource (HR) professionals in the banking sector of Hyderabad, Pakistan. Data was analyzed using thematic analysis in NVivo 12. The findings revealed three traditional recruitment challenges and processes, ethical considerations, risks, challenges as well as future trends and perspectives. The results revealed that AI has the potential to make recruitment more efficient through automated candidate filtering, selection matching, and initial screening. This helps reduce delays and minimize bias. However, concerns were raised about employee data privacy and job insecurity associated with automation. The study emphasized the need for industry-specific metrics to guide effective AI implementation. It also highlighted how AI can support performance management by allowing HR teams to detect early signs of employee dissatisfaction. While AI may enhance career development and workplace motivation, its role in automating administrative tasks could also lead towards ethical dilemmas, especially related to job displacement. To address these challenges, the study recommended updating HRM practices to include employee protection strategies, ensuring a balance between technological advancement and workforce well-being.
Downloads
Published
How to Cite
Issue
Section
License
Thus, work submitted to Journal of Management and Research implies that it is original, unpublished work of the authors; neither published previously nor accepted/under consideration for publication elsewhere.

