Umaal Ahmed Khan

Employers increasingly provide training for working with digital technologies and artificial intelligence (AI), but it is unclear whether the same provision benefits all workers equally. Integrating the job demands–resources (JD-R) model with Sen’s capability approach, this study treats workplace AI exposure as a potential job demand, digital skills and employer-provided digital training as resources, capability-relevant wellbeing as the outcome, and social class as a proxy for the conversion conditions under which resources are used to ensure wellbeing. Structural equation models with ordinal indicators were estimated for 8065 employees in 27 EU countries (Special Eurobarometer 101.4), with country fixed effects, country-clustered and delete-one-country jackknife standard errors, and Random Forest and SHAP analyses as robustness checks. AI exposure was weakly and negatively associated with wellbeing (β = −0.073) and explained almost none of the variance in AI threat appraisal (R² = 0.002). Employer-provided digital training (β = 0.209) and digital skills (β = 0.189) were the strongest workplace correlates of wellbeing and were robust to every specification. With scalar measurement invariance established, multi-group models showed that the association between employer-provided training and wellbeing was weaker among working-class than among middle-class employees (0.072 versus 0.130; Wald p = 0.001, jackknife p = 0.012), and the model explained 12.0% of working-class wellbeing compared with 31.1% among upper-class employees. The pattern suggests that equal provision of employer digital training may not yield equal benefit, although the class difference is consistent in direction rather than statistically conclusive across all specifications.

Background: The increasing adoption of artificial intelligence (AI) in organizations has significantly transformed work processes and employee experience. However, the successful implementation of AI depends not only on the availability of technologies but also on how employees perceive and respond to AI systems. In this context, organizational support, digital competencies, and confidence in AI governance may shape employee readiness for AI-enabled workplaces. Objective: This study examines the relationships between employer-provided AI support, employees’ digital skills, and attitudes toward AI, with particular attention to the mediating role of digital skills and the moderating role of perceptions of AI regulations. Methods: Using cross-sectional data from the 2024 Special Eurobarometer 554 survey, collected from 7,942 employees across 27 European Union countries, the study employs Partial Least Squares Structural Equation Modeling within the framework of Job Demands-Resources theory. Results: The findings indicate that employer-provided AI support is positively associated with employees’ digital skills, which in turn are linked to more positive attitudes toward AI. Digital skills partially mediate this relationship, accounting for 51.12% of the total effect. Additionally, perceptions of AI regulations modestly moderate the relationship between digital skills and employees’ attitudes toward AI. Conclusions: The results imply that organizations and policymakers should place greater emphasis on employee upskilling, continuous training initiatives, digital competency development, and transparent AI governance to cultivate more positive employee attitudes toward AI. These factors play a complementary and equally critical role in supporting the effective and sustainable integration of AI technologies within workplace environments.

This study investigates the relationship between foreign direct investment (FDI), institutional quality, industrialization, and carbon emissions across 48 high-income and 37 upper-middle-income countries for the years 2002 to 2022 by employing panel quantile regression analysis using R software. The results show that inward FDI has increased pollution in high-income countries by the coefficient of 0.016 to 0.026 while it has reduced carbon emissions in upper-middle-income countries by the coefficient of -0.012 to 0.01. In outward FDI, although it is expected that upper-middle income countries will end up with low carbon emissions, the results show that carbon emissions increase in these countries by the coefficient of -0.025 to 0.08. Industrialization has significantly raised pollution in both groups, while institutional quality has a positive impact in high-income countries and a negative influence in upper-middle-income nations, implying the mixed impact of good governance in environmental management. The findings highlight the dual effect of FDI on carbon emissions, indicating that its environmental impact varies according to the extent of policy interventions, i.e. carbon taxation, environmental regulation, designed to balance economic growth with environmental protection. The results offer valuable insights for companies and policymakers seeking to align economic growth with environmental sustainability across different stages of economic development.