Artificial Intelligence-Driven HR Practices in SMEs: A PRISMA-Compliant Scoping Literature Review

Abstract

Artificial intelligence (AI) is rapidly reshaping human resource management (HRM) practices, extending its reach even to small and medium-sized enterprises (SMEs). Despite the prevalence of AI in HRM, its integration into the practices of SMEs, traditionally characterized by limited HR resources, remains an understudied area in scientific literature. A knowledge gap was identified through a Scopus database search, revealing a lack of comprehensive exploration into emerging trends related to AI’s impact on hiring, skill assessment, bias mitigation, and time constraints in SMEs. This study aims to address this gap by conducting a methodical analysis and synthesis of existing scientific contributions on the adoption of AI in SMEs for HR purposes. Employing a rigorous scoping literature review grounded in the PRISMA protocol, the investigation focuses on peer-reviewed publications in English, indexed in the Scopus database. The findings, encompassing emerging publications, authors, key concepts, and avenues for future research, offer valuable insights for HR professionals, entrepreneurs, and the scientific community. This study not only contributes to the understanding of AI’s impact on grassroots HR processes in small organizations but also provides practical guidance and recommendations for optimization and enhancement.