As global economies accelerate their digital transformation, artificial intelligence (AI) technologies have become a key driver of innovation and economic growth, especially in the electronic commerce sector. This study examines the impact of AI applications in marketing and sales on e-commerce performance across European economies, using official data from Eurostat. Our methodology includes factor analysis to identify underlying data structures, linear regression to explore causal relationships, generalized linear model (GLM) multivariate analysis to assess the combined effect of multiple factors, and cluster analysis to categorize countries based on their level of digitalization. Our results demonstrate a strong correlation between AI use and e-commerce performance, revealing two distinct clusters with unique characteristics. The findings reveal a positive association between the use of AI and firms’ engagement in e-commerce activities, although the influence on turnover appears more limited. This suggests that while AI facilitates entry into the digital marketplace, financial performance depends on a broader set of factors, including technological infrastructure, market readiness, and strategic alignment. These insights provide a solid basis for developing policies and strategies that support digital transformation and technological innovation in Europe, helping to build competitive and sustainable economies.

Generative artificial intelligence is gradually infiltrating contemporary socio-technical systems, affecting work practices, labor market participation, and the dynamics of labor-related costs. In this paper, we analyze cross-sectional relationships between generative AI use among active individuals and two macro-level labor-market indicators: the labor force participation rate and the evolution of nominal unit labor costs. The research is based on comparative European data. It analyses the use of AI in personal, professional, educational, and recent contexts as an expression of the interaction of human agency, technological infrastructure, and the institutional environment. The methodology combines multivariate modelling and regression with exploratory factor analysis and clustering to examine the statistical associations between AI use and labour-market indicators, as well as the emergent typologies of countries with diverse profiles. Results indicate stable links between the extent of generative AI use and employment, and unit labour cost disparities, suggesting that generative AI use is associated with broader socio-economic development patterns, without implying a causal relationship. The results highlight the need for an integrative view of AI adoption, linking human behaviors to organizational procedures and governance structures to ensure a responsible and fair transition.

This study examines the relationship between individuals’ perceptions of corporate social responsibility (CSR) and their job-seeking intentions, with a particular focus on the mediating role of personal values and attitudes toward social responsibility. The research was conducted in Romania’s south-west region between June and September 2025, using a stratified sample of 453 respondents. Data were analyzed using SMART-PLS 3.0 through structural equation modeling. The results indicate a positive association between perceived CSR and job-seeking intention, with personal values and attitudes toward CSR significantly mediating this relationship. The findings suggest that participants in this study who perceive organizations as socially responsible also report higher levels of organizational attractiveness, particularly when there is alignment between personal and organizational values. At the same time, the results highlight that consistent CSR practices are associated with stronger perceptions of employer attractiveness. Overall, the study suggests that CSR is closely linked to employment-related attitudes and intentions, supporting the view that alignment between individual values and organizational ethical principles represents an important dimension of contemporary human resource strategies.