Between Acceptance and Skepticism: Human Resources Professionals’ Sensemaking of Artificial Intelligence in Recruitment
TL;DR
The study suggests that acceptance does not arise solely through conviction but may also develop through a provisional, habituation-like process conceptually distinct from quality updating and social normalization within the legally and culturally distinctive context of German-speaking countries.
Abstract
The increasing diffusion of artificial intelligence in recruitment has attracted considerable scholarly and practical attention, while the ways in which human resources (HR) professionals subjectively interpret and integrate these technologies into their professional practice remain insufficiently understood. Against this background, the present study investigates how HR professionals make sense of artificial intelligence use in recruitment while navigating an enduring tension between acceptance and skepticism. Methodologically, the study adopts a constructivist-interpretive research design grounded in Weick’s sensemaking framework. Eleven semi-structured expert interviews with HR professionals from Germany and Austria were analyzed using qualitative content analysis, complemented by a theory-guided interpretive sensemaking analysis. The findings identify six overarching sensemaking patterns: identity protection, retrospective key moments, active co-creation of uncertainty, social embeddedness, sustained ambivalence, and plausibility-seeking through metaphor. These patterns condense into four participant-anchored interpretive types: Guardians, Wait-and-Seers, Cautious Integrators, and Full Integrators. Professional identity emerged as the central interpretive frame shaping participants’ evaluations of artificial intelligence. Furthermore, the study suggests that acceptance does not arise solely through conviction but may also develop through a provisional, habituation-like process conceptually distinct from quality updating and social normalization. These findings carry important implications for the governance of artificial intelligence-supported recruitment processes. From a practical perspective, the study highlights the importance of identity-sensitive change management, structured spaces for reflection, staged experimentation, and mandatory critical-review mechanisms aimed at preventing the habituation-like erosion of human oversight. The study contributes to the emerging literature at the intersection of sensemaking, professional identity, and artificial intelligence acceptance in recruitment, while extending existing acceptance research by foregrounding a provisional, habituation-like pathway of adoption within the legally and culturally distinctive context of German-speaking countries.