Artificial Intelligence in Human Resource Management: Opportunities for Digital Transformation and Administrative Performance Improvement among Employees in the Palestinian Health Sector

Abstract

Global healthcare systems are undergoing rapid digital transformation, driven by ongoing advancements in Artificial Intelligence (AI), which now extend beyond clinical applications to administrative domains—particularly Human Resource Management (HRM). In light of the structural challenges facing the Palestinian health sector in managing human capital, this study aims to address a knowledge gap concerning the strategic potential of AI to enhance administrative efficiency and improve HRM practices. The study investigates the practical impact of AI applications on administrative processes in healthcare institutions, focusing on strengthening institutional communication, motivating employees, and improving productivity. A mixed-method research design was adopted using a Concurrent Triangulation Strategy (CTS), combining quantitative data from an online questionnaire with qualitative insights gathered through expert interviews using the Delphi method. The quantitative sample included 75 participants from administrative and HR leadership roles in hospitals, while the qualitative sample consisted of 43 purposefully selected individuals—including AI experts and HR professionals from both Palestine and abroad—representing diverse experiences in digital transformation. A systematic literature review was conducted following the PRISMA model (Preferred Reporting Items for Systematic Reviews and Meta-Analyses), and data were analyzed using SPSS V.26 for quantitative analysis and MAXQDA 2020 for qualitative analysis. Findings indicate that successful AI adoption in HRM depends primarily on enhancing digital competencies, promoting institutional awareness of automation, and securing appropriate technological infrastructure. The study found minimal variance in participants’ responses based on gender or age, suggesting that institutional factors outweigh demographic ones in influencing digital transformation outcomes. However, notable challenges were identified, including a shortage of digital expertise, high infrastructure costs, and the absence of a regulatory framework for AI implementation. The study recommends formulating a comprehensive national strategy focused on capacity building, policy development, and strengthening public-private partnerships. On a practical level, the study proposes a three-phase Digital Transformation Roadmap (DTR): establishing digital infrastructure, building institutional capacity, and conducting periodic performance-based evaluations. Additional recommendations include revising job descriptions to integrate digital skills, developing tools to measure Return on Investment (ROI) in AI, and fostering a culture of innovation. The study concludes with future research directions, including cross-sectoral comparisons, longitudinal assessments of AI’s sustainable impact, and investigations into the psychological and behavioral dimensions of HR automation.