Developing AI-Ready Human Capital for Future Work: An HRM Perspective on Entrepreneurial AI Value Among Female Business Students in Kuwait

Artificial intelligence (AI) is reshaping occupational tasks and skill requirements, creating a human resource management (HRM) challenge around how future employees develop readiness for responsible AI-enabled work. This study examines relationships among perceived AI readiness (PAIR), perceived entrepreneurial AI value (AIV), and future AI-enabled work and entrepreneurial engagement (FAE) among 407 female business students in Kuwait. Five-category ordinal indicators were analyzed using diagonally weighted least squares confirmatory factor analysis, competing measurement models, bootstrap-based latent indirect-effect analysis, and an extended structural model incorporating AI learning exposure, trust in AI task delegation, and job-displacement concern. A three-factor readiness–value–engagement structure was retained, although discriminant validity between AIV and FAE was qualified by a high latent correlation. The retained structure showed mixed robust fit and substantial shared covariance, warranting cautious interpretation. PAIR was positively associated with AIV, which was strongly associated with FAE. The indirect association remained significant after supplementary variables were included, decreasing from β = 0.650 to β = 0.420. Formal AI learning exposure was positively associated with readiness but showed a small negative conditional association with perceived entrepreneurial AI value after readiness was held constant; this exploratory finding requires replication. Trust was positively associated with readiness, value, and engagement, while job-displacement concern coexisted with higher readiness and value. Findings suggest that AI-ready human-capital development should combine exposure with authentic business applications, critical evaluation, calibrated trust, and responsible human–AI collaboration.