Ardio Rizky Tansil, Tan
Universitas Sangga Buana Bandung, Indonesia

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

Artificial Intelligence in Hospital Human Resource Management: A Systematic Review and Bibliometric Analysis Kosasih Kosasih; Marisa Yesika; Fana Afizza Lustina; Efi Rusdiana; Ardio Rizky Tansil, Tan
Advances in Human Resource Management Research Vol. 4 No. 2 (2026): February - May
Publisher : Yayasan Pendidikan Bukhari Dwi Muslim

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60079/ahrmr.v4i2.776

Abstract

Purpose: This study examines research trends on the application of Artificial Intelligence (AI) in hospital human resource management (HRM) and explores its implications for employee performance and career development. Research Design and Methodology: A Systematic Literature Review (SLR) and bibliometric analysis were conducted on 30 articles published between 2020 and 2025. Relevant studies were identified through a structured keyword search and screened using the PRISMA protocol. VOSviewer was employed to map research trends, thematic clusters, and keyword relationships. Findings and Discussion: our major research clusters were identified: AI and employee performance, AI in recruitment and talent management, career development and employee engagement, and digital transformation with data analytics. Publications increased substantially after 2023, reflecting growing interest in AI-driven HRM. The literature indicates a shift from operational efficiency and automation toward strategic workforce management, data-driven decision-making, talent optimization, and sustainable career development. AI is increasingly recognized as a tool for enhancing organizational adaptability and human capital effectiveness in hospitals. Implications: Healthcare organizations should integrate AI with workforce capabilities and organizational readiness to improve employee performance and support sustainable career development. Originality: This study provides a comprehensive synthesis of AI research in hospital HRM by combining PRISMA-based review procedures with bibliometric analysis.