Women's Career Resilience in AI-Driven Work: The Roles of Usefulness and Job Demand

Abstract

This research investigates how Perceived Usefulness and Job Demand shape Women's Career Resilience, with Artificial Intelligence Usage examined as the mediating mechanism among women employed in Indonesia's digital business sector. Grounded in the Technology Acceptance Model (Davis, 1989) and the Job Demands-Resources Model (Bakker & Demerouti, 2014), the study evaluated five hypotheses through Partial Least Squares Structural Equation Modeling (PLS-SEM) using SmartPLS 4.0. A sample of 205 women who actively use AI in their daily work provided responses through an online questionnaire. Results confirm that Perceived Usefulness (β = 0.414, p < 0.001) and Job Demand (β = 0.250, p < 0.001) significantly influence AI Usage, which in turn significantly influences Career Resilience (β = 0.332, p < 0.001). AI Usage partially mediates both relationships (β = 0.138 and β = 0.083, respectively). These findings indicate that AI adoption, whether driven by positive technology perception or occupational pressure, serves as a behavioral mechanism that strengthens women's career resilience amid digital transformation.