Work

How does employer AI support influence digital skills and AI attitudes of employees in European countries: A PLS-SEM analysis

Year: 2026
Type: article
Study design: Observational Study
Abstract: 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.
Language: English
Open Access status: hybrid
Estimated APC paid: $3,650
OpenAlex ID: W7166473528
FWCI: 10.07
Cites: 35
Cited by: 1
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