THE FUTURE RESEARCH DIRECTIONS ON THE USE OF AI IN HRM: A SYSTEMATIC REVIEW. AN EXPLORATION OF THE DARK SIDE.

Abstract

The rapid integration of artificial intelligence (AI) into Human Resource Management (HRM) has revolutionized practices such as recruitment, performance monitoring, and decision-making, yet it introduces significant ethical and operational risks. This systematic review explores the "dark side" of AI in HRM, synthesizing 22 articles (2021–2024) through a hybrid bibliometric and TCM-ADO framework analysis to map evolving research themes, methodologies, and future directions. The study identifies five critical research clusters: (1) algorithmic impacts, (2) bias, fairness, privacy, and transparency, (3) ethical theories, (4) employee attitudes and trust, and (5) organizational change. Findings reveal AI’s dual role in enhancing efficiency while perpetuating biases, eroding privacy, and fostering employee distrust due to opaque "black-box" systems. Ethical concerns, such as dehumanization and surveillance, underscore the need for explainable AI (XAI), stakeholder collaboration, and robust governance frameworks.

Methodologically, the review combines quantitative analyses (e.g., structural equation modeling) with qualitative insights (e.g., abductive case studies), highlighting interdisciplinary approaches to address AI’s complexity. Key outcomes emphasize HR’s evolving role from administrative to strategic oversight, prioritizing human-centric adoption, employee well-being, and ethical compliance. Challenges include resistance from job displacement fears, algorithmic opacity, and cultural adaptation, while enablers involve leadership commitment, upskilling, and inclusive design.

Future research must prioritize transparency, cross-cultural validity of models, and participatory AI development to mitigate risks. Theoretical contributions advocate integrating ethics (deontology, Rawlsian fairness) with technological innovation, while practical implications stress GDPR-inspired data governance and policies regulating intrusive AI tools. This review calls for balanced AI deployment that harmonizes efficiency with equity, fostering trust and sustainability. By addressing these dimensions, organizations can navigate AI’s transformative potential while safeguarding ethical standards and employee welfare, ensuring HRM’s evolution aligns with human dignity and organizational resilience.