Artificial Intelligence (AI) is increasingly influencing Human Resource Management (HRM), yet evidence from small and medium enterprises (SMEs) in the manufacturing sector remains scarce, particularly across different national contexts. This paper presents preliminary findings from a cross-national survey comparing AI adoption in HRM among manufacturing SMEs in Italy and Finland. The study examines how AI is being adopted in manufacturing SMEs, explores the reasons behind non-adoption, and reflects on some ethical implications of AI-driven HRM. Findings reveal that Finnish SMEs tend to adopt AI more broadly across HRM practices, while adoption in Italian SMEs is heterogeneous. Among non-adopters, the main barriers include limited digital skills, insufficient technological knowledge, and difficulties in integrating AI strategically. These findings offer practical insights for managers and policymakers and contribute to the growing conversation on context-sensitive AI adoption in HRM practices.
Exploring AI Adoption in HRM: Preliminary Evidence from Italian and Finnish manufacturing SMEs
Adnan Hussain
Writing – Original Draft Preparation
;Patrizia Garengo
Supervision
;
In corso di stampa
Abstract
Artificial Intelligence (AI) is increasingly influencing Human Resource Management (HRM), yet evidence from small and medium enterprises (SMEs) in the manufacturing sector remains scarce, particularly across different national contexts. This paper presents preliminary findings from a cross-national survey comparing AI adoption in HRM among manufacturing SMEs in Italy and Finland. The study examines how AI is being adopted in manufacturing SMEs, explores the reasons behind non-adoption, and reflects on some ethical implications of AI-driven HRM. Findings reveal that Finnish SMEs tend to adopt AI more broadly across HRM practices, while adoption in Italian SMEs is heterogeneous. Among non-adopters, the main barriers include limited digital skills, insufficient technological knowledge, and difficulties in integrating AI strategically. These findings offer practical insights for managers and policymakers and contribute to the growing conversation on context-sensitive AI adoption in HRM practices.Pubblicazioni consigliate
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