Abstract:

Artificial intelligence and algorithmic systems are increasingly integrated into workplace coordination, evaluation, and decision-making processes (Kellogg et al., 2020; Parent-Rocheleau & Parker, 2022). While prior research has examined algorithmic management primarily in platform and gig-work settings, less is known about how employees interpret AI-supported management systems in more conventional organizational contexts.
This research-in-progress explores employee perceptions and experiences of AI-enabled managerial systems and considers how these interpretations may shape workplace experiences, including trust, identity, and perceptions of meaningful work. Drawing on research on algorithmic management, legitimacy, and organizational sensemaking, the paper argues that employee responses to AI systems depend not only on system functionality, but also on how such systems are understood and experienced within organizational life.