Employing Artificial Intelligence in Recruitment: Modifying Human Resource Decision Making in Banking Sector

Abstract

Artificial Intelligence (AI) has been widely used in recruitment and talent acquisition in the banking industry, which is experiencing a rapid digital transformation as part of the Industry 4.0. But there is still not enough empirical evidence to confirm the effectiveness of using AI in recruitment tools to enhance the quality of HR decisions in this evolving economy context. The present research investigates the positive impact of HR Professional Acceptance in the direction of AI-Enabled Recruitment Practices and further HR Decision-Making Quality and evaluates Ethical and Data-Privacy Concerns as a moderating boundary condition. Using the Technology Acceptance Model (TAM) and Resource-Based View (RBV), a quantitative cross-sectional design was used, and data was collected from 300 HR professionals from conventional & Islamic banks in Islamabad, Pakistan. All four hypotheses were supported in the OLS multiple regression, mediation and moderation analyses. HR Professional Acceptance had a strong positive correlation with AI Adoption (r = 0.499, p < 0.001). The best predictor of decision quality was AI-Enabled Practices (β = 0.417, p < 0.001) with partial mediation being confirmed. This relationship was significantly and negatively moderated by Ethical and Data-Privacy Concerns (β = −0.229, p < 0.001). The model explained 32.95% of the variance in HR Decision-Making Quality (F (3, 296) = 48.49, p < 0.001). The results suggest that trust is not enough, but that active AI deployment leads to positive quality outcomes, and that moral anxiety has a negative impact on those outcomes. The study has both theoretical and practical contributions, as it introduces decision quality as the key performance outcome in the TAM and offers a governance pathway for banks in Pakistan and government authorities.