Purpose Persistent shortages and high turnover among construction managers have made work-life outcomes a critical concern for both organizational performance and safety. This study investigates whether and how generative artificial intelligence (GenAI) can serve as a lever for creating more sustainable managerial roles within construction organizations. It approaches GenAI not merely as a technical innovation but as a socio-organizational phenomenon that reshapes managerial experience. Design/methodology/approach Using a quantitative cross-sectional survey design, the research examines the relationship between itemized GenAI competencies and validated constructs of work-life quality and work-life balance among construction managers. Findings The findings reveal a strong and positive association between GenAI adoption and both dimensions of managerial well-being. Predictive scheduling, documentation automation, and design support emerged as the most influential applications, underscoring that not all AI tools contribute equally to improved work-life outcomes. Machine learning models – particularly random forests – demonstrate the non-linear and complex nature of these relationships, while high internal reliability of the constructs strengthens the empirical foundation of the results. Research limitations/implications From a research perspective, the study contributes novel empirical evidence to the discourse on digital transformation in construction by shifting attention from productivity metrics to human-centered outcomes. It demonstrates that GenAI adoption is not only an operational enhancer but also a determinant of occupational well-being. Practical implications Practically, the study offers actionable insights for construction firms seeking to enhance managerial retention and satisfaction: responsible deployment of GenAI can improve efficiency and well-being simultaneously when supported by sound governance and equitable access. However, the benefits are not automatic. Sustained value creation depends on addressing ethical risks, transparency, and the uneven distribution of technological gains across roles and organizations. Originality/value By linking specific AI applications to distinct work-life outcomes, this study advances the field beyond generalized claims about “AI use” toward a more nuanced understanding of technology's human implications. The study thus positions GenAI as a credible, evidence-based pathway to sustainable managerial work in the construction sector.
Olugboyega et al. (Tue,) studied this question.