Generative AI utilization and employee productivity through digital skills with the moderating role of AI trust

Counts differ because each database indexes a different set of publications. We treat OpenAlex as the canonical count; Google Scholar is not shown (no API, and crawling it violates its ToS).

Generative AI adoption has attracted considerable scholarly and managerial attention because of its potential to improve employee productivity. However, empirical evidence remains limited regarding how different dimensions of generative AI adoption relate to employee productivity, particularly in developing contexts. Drawing on Task–Technology Fit Theory and Social Cognitive Theory, this study examines the associations between the frequency, depth, and purpose of generative AI adoption and employee productivity, with digital skills as a mediator and AI trust as a moderator. A cross-sectional survey of 404 employees from generative AI-enabled organizations in Kabul, Afghanistan, was analyzed using SEM. The findings show that the frequency and depth of generative AI adoption are positively associated with employee productivity, whereas the purpose of AI adoption has no significant direct association. Digital skills demonstrate significant indirect associations between generative AI adoption and employee productivity, while AI trust does not significantly moderate these relationships. The study contributes to the literature by conceptualizing generative AI adoption as a multidimensional construct and emphasizing the role of employees’ digital skills in AI-driven workplaces. Practically, the findings help identify ways to improve employees’ digital skills to ensure generative AI adoption and reap the associated benefits, supporting sustainable digital transformation. Thus, it contributes to the United Nations Sustainable Development Goals (SDGs), specifically SDG 8 (Decent Work and Economic Growth) and 9 (Industry, Innovation and Infrastructure).