Leveraging Artificial Intelligence for Talent Acquisition: Insights from an HR Perspective in the Banking Sector

Abstract

 The incorporation of automatic procedures has become increasingly necessary in the modern financial setting; nonetheless, traditional systems may prove ineffective and subjective. The main objective of the current study is to investigate the utilization of artificial intelligence (AI) in recruitment from the human resource standpoint in Bank Muscat, Oman. Quantitative data was collected through the use of questionnaires administered to 55 respondents, including qualified individuals in human resource department and job seekers. Data collection involved use of IBM SPSS AMOS software and Microsoft Excel to estimate path parameters in the structural equation modeling technique. It was found out that the results of path analysis SEM revealed an extremely high goodness of fit, explaining 75% of the variance in the automation of recruitment (R2 = 0.75). The results from the inferential parameter test indicate that achieving a balance between various trade-offs in operations (Benefit_Challenges: β = 0.354, p = 0.003), followed by the implementation of appropriate technologies for automation (AI_Tool: β = 0.303, p = 0.005) and contemporary organizational policies (HR_Practices: β = 0.269, p = 0.013), were the most significant structural factors affecting success in using automation. However, institutional understanding and experience with automation (Role_of_AI: β = 0.080, p = 0.480) did not significantly influence the efficiency of recruiting procedures. While AI makes recruiting procedures quicker and unbiased, and creates data-driven routes, the problems related to technology ignorance and job security still prevail. Overall, it is concluded that ensuring maximum validity in talent selection in Omani banks in the long term would mean moving away from general theoretical awareness and toward implementation, training, and hybrid approaches involving both human and artificial intelligence.