Owning Work in Human-AI Collaboration: Psychological Ownership and Emotional Consequences

Drawing on psychological ownership theory, this study examines how AI integration into professional work reshapes job-based psychological ownership and the affective consequences of this disruption. We argue that job-based psychological ownership, grounded in control, job-relevant knowledge, and self-investment, becomes disrupted when AI intervenes in core work activities. We employ a multi-study research design, combining two qualitative case studies and an experimental study, with additional studies currently underway. The qualitative studies examine legal professionals and marketing professionals in Azerbaijan, revealing how AI reshapes ownership by redistributing control, expertise (knowing what to do), and effort between humans and technologies. Across both professional contexts, ownership was preserved when individuals retained control over task direction and decision-making, applied their expertise, and invested personal effort, but diminished when AI assumed responsibility for defining task substance, executing work with minimal human involvement, or providing substantive advice on what to do. Reduced ownership was consistently associated with diminished feelings of accomplishment and pride. Building on these insights, an experimental study using a professional task simulation provides initial causal evidence that reduced control over AI-supported outputs increases negative self-conscious emotions, particularly shame. The findings highlight ownership as a critical mechanism linking AI integration to professionals’ emotional experiences of work, with implications for human-AI collaboration and the future of work.