Artificial intelligence in learning and work practices: urban–rural differences in perceived productivity and competitiveness

Aim: Artificial intelligence (AI) is increasingly shaping learning processes and work practices, with important implications for productivity and regional competitiveness. However, the benefits of AI adoption may not be evenly distributed across urban and rural contexts. This study examines how individuals living in large cities, small cities, and rural areas perceive and use AI in learning and professional activities, and how they evaluate its economic benefits and associated risks. Method: The study is based on an online survey conducted in 2025 in Lithuania, comprising 17 Likert-scale items measuring perceived productivity benefits, learning support,
digital skills, the future relevance of AI, and perceived risks. The final sample comprised 120 valid and fully completed responses (N = 120). Descriptive statistics were used to summarize response patterns, and pairwise Welch’s t-tests were applied to explore differences across residential contexts. Results: The results indicate generally positive attitudes toward AI across all groups, particularly regarding overall time-saving, improved decision-making, and enhanced competitiveness. Statistically significant differences were observed only between respondents living in large cities and small cities, with greater concern about potential job displacement. Conclusions: Overall, the findings of the sample suggest that while AI is widely perceived as a generally productivity-enhancing tool across regions, place-based disparities in skills and perceptions persist, underscoring the need for targeted training, institutional support, and inclusive digital policies to strengthen balanced regional competitiveness.