Smart tools for diverse minds: how AI use impacts performance and well-being among neurodivergent employees
Lu (Lucy) Xing, Kahn TaskerPurpose
This study investigates how and when AI use at work relates to neurodivergent employees’ task performance and burnout. Drawing on Sociotechnical System Theory, the study proposes that executive functioning (EF) serves as the mediating mechanism and that social support serves as the moderating factor.
Design/methodology/approach
The three-wave survey data were collected from 286 neurodivergent employees in the United Kingdom, enabling temporal separation of the predictor, mediator, and outcome variables to reduce concerns for common method bias.
Findings
Results showed that AI use at work was positively associated with EF, which in turn was positively associated with task performance and negatively associated with burnout. Social support moderated these relationships, with AI use’s benefits for EF and subsequent performance and well-being emerging only when workplace social support was high.
Originality/value
This study advances a sociotechnical understanding of how AI use may support neurodivergent employees. By positioning AI as external cognitive scaffolding and social support as a key social system, the study clarifies how technological and social systems work together to shape work outcomes among neurodivergent employees.