Stakeholder-specific adoption of AI in HRM: workers’ representatives’ perspective on concerns, requirements, and measures - Malin, Christine; Fleiß, Jürgen; Thalmann, Stefan (Frontiers in Artificial Intelligence, 2025)
IntroductionAI regulations aim to balance AI’s potential and risks in general and human resource management (HRM) in particular. However, regulations are not finally defined and the perspectives of key stakeholders of HRM applications are not clear yet. Research on AI in HRM contributes only to a limited extent to the understanding of key HRM stakeholders, and the perspective of workers’ representatives is especially lacking so far.MethodsThis paper presents a study of three focus group workshops investigating workers’ representatives’ perspectives, to determine which concerns they perceive when using AI in HRM, which resulting requirements they have for adopting AI in HRM, and which measures they perceive as most suitable to fulfill them.ResultsOur results revealed that workers’ representatives were critical of using AI across all HRM phases, particularly in personnel selection. We identified requirements and measures for adopting AI in HRM from the perspective of workers’ representatives. These were summarized in a catalog including six dimensions: control, human oversight, responsibilities, transparency and explainability, lawful AI, and data security.DiscussionOur findings shed a nuanced light on workers’ representatives’ needs, providing relevant insights for research on stakeholder-oriented adoption of AI in HRM and for specifying current AI regulations.