AI-Mediated Participation and People Sustainability: A Socio-Technical Case Study in Healthcare Shift Scheduling

Artificial intelligence (AI) is increasingly reshaping organizational dynamics, not only through efficiency gains but by influencing how work is structured, interpreted, and experienced. In healthcare, where professional team stability is crucial, this transformation intersects with structural issues such as persistent nurse turnover. This study presents an exploratory case study of a private accredited hospital in Italy that introduced an AI-enabled shift scheduling system (“Dream-Shift”) in response to perceived inequities and workforce instability. The system was embedded in a participatory architecture that included a Nursing Practice Council and HR dashboards to visualize staffing patterns. Drawing on theories of Sustainable Human Resource Management (SHRM), algorithmic management, and people sustainability, the study examines how AI-mediated transparency and participation affect fairness perceptions, predictability, and organizational climate. Using administrative data, ethnographic observations, internal documents, and informal feedback, the study finds that the algorithm did not eliminate all inequities but made decision constraints visible and debatable. It redistributed the emotional burden of scheduling and enabled more structured conversations about work. Managers transitioned from unilateral decision-makers to facilitators of collective interpretation. The results suggest that when integrated into participatory infrastructures, AI can foster organizational transparency, support relational stability, and act as a socio-technical enabler of people sustainability rather than as a tool of control.