From office to living room: linking AI awareness and career sustainability from a work–family boundary perspective

Purpose Drawing upon work–family boundary theory and the significance of employees career sustainability amid widespread artificial intelligence (AI) adoption, this study examines the impact of AI awareness on two indicators of career sustainability (i.e. well-being and productivity) via work–family conflict and the moderating role of work–family segmentation preference in this relationship. Design/methodology/approach We collected data from 421 subordinate-supervisor dyads across multiple industries using a two-wave design and tested the hypotheses with structural equation modeling in Mplus. Findings The results indicated a negative effect of AI awareness on career sustainability (i.e. subordinate-rated well-being and supervisor-rated productivity) via work–family conflict. Additionally, work–family segmentation preference functions as an important boundary condition, weakening the positive relationship between AI awareness and work–family conflict and attenuating the indirect negative effect of AI awareness on both well-being and productivity. Research limitations/implications This study offers three key theoretical contributions. First, it identifies AI awareness as a novel antecedent of career sustainability, extending research within socio-technical organizational contexts. Second, drawing on work–family boundary theory, it reveals a cross-domain spillover mechanism through which AI awareness undermines career sustainability via work–family conflict. Finally, it highlights work–family segmentation preference as a boundary management strategy that buffers the negative effects of AI awareness, enriching understanding of individual-level moderators in AI-related career research. Practical implications This study offers several practical implications. First, organizations should mitigate the negative impact of AI awareness on career sustainability by fostering balanced human–AI collaboration through clear job design, AI literacy training, and supportive feedback systems. Second, promoting work–family boundary management – such as, encouraging segmentation preferences and family-supportive policies – can reduce work–family conflict and enhance employee well-being. Finally, integrating boundary management skills into recruitment and development practices helps organizations sustain both employee happiness and productivity in AI-driven workplaces. Social implications As AI becomes increasingly embedded in workplaces, its influence extends beyond productivity to employees' family life and long-term career sustainability. This study suggests that unmanaged AI-related stress may erode well-being and work effectiveness through work–family conflict. The findings highlight the broader social need to promote healthier human–AI collaboration, clearer work–life boundaries, and more sustainable career development. By encouraging AI literacy, boundary management, and supportive organizational norms, organizations can help reduce the unintended social costs of technological disruption and foster employee well-being, family harmony, and sustainable employment in the AI era. Originality/value Our study contributes to career sustainability research by identifying AI awareness as a novel antecedent in socio-technical workplaces. Additionally, we reveal a cross-domain spillover mechanism through which AI awareness undermines employees' career sustainability via work–family conflict. Furthermore, we identify work–family segmentation preference as an individual boundary management strategy that buffers the negative spillover effects of AI awareness.