Abstract:

Rapid technological and organizational changes have intensified concerns regarding new forms of digital exclusion, particularly inequalities in individuals’ ability to convert human and social capital into perceived employability. This study examines how three forms of human capital (education, English proficiency, and AI skills) and two forms of social capital (bonding and bridging) shape employability across Generations Z, Y, and X. Although employability has traditionally been understood as a function of formal education and labor-market experience, constant technological evolution and shifting opportunity structures suggest that different resources may matter for different age groups.

Based on a national online survey of 723 Israeli adults aged 18–60, separate linear regression models were estimated for each generational cohort. Across all groups, AI skills emerged as a significant predictor of perceived employability, although the strength of the association varied by age. The largest effect was observed among Generation X, indicating that technological competence plays a compensatory role for individuals whose careers began before the rise of AI-centered work practices. For Generations Y and Z, AI skills remained important but were more moderately associated with employability, reflecting their earlier and more routine exposure to technologically mediated environments.

Bonding social capital was a strong and consistent predictor of employability across all generations, underscoring the centrality of trust-rich, supportive relationships for navigating uncertain labor-market conditions. In contrast, bridging social capital did not contribute positively to employability in any cohort and was significantly negative for Generation Y. This pattern contradicts classical theories that emphasize the universal advantages of weak ties and suggests that loose, heterogeneous networks may not translate into concrete opportunities within contemporary, AI-intensive labor markets. Traditional forms of human capital, namely education and English proficiency, did not significantly predict employability for any generation, indicating a structural shift in how labor-market resources are valued.

Together, the findings highlight that generationally specific patterns of human and social capital produce distinct forms of digital exclusion, reflected in unequal capacities to maintain or enhance perceived employability in rapidly changing technological environments.

Keywords:

AI skills, generational cohorts, employability, digital exclusion, bonding capital, bridging capital.