Research objectives and hypothesis/research questions:
The study aims to identify patterns of AI usage among young adults, examine the relationship between usage intensity and user attitudes, and identify distinct user segments. Hypotheses were formulated assuming a positive relationship between AI usage intensity and positive attitudes toward artificial intelligence. The study had a quantitative and exploratory character.

Research methods:
The study was conducted on a purposive sample of 120 respondents (mean age = 23.3) using a self-developed, single-item online questionnaire. The analysis included descriptive statistics, Pearson correlation, linear regression, and cluster analysis (k-means), incorporating both behavioral and affective variables.

Main results:
The results indicate moderately positive attitudes toward AI alongside varying levels of usage. A significant positive relationship was found between AI usage frequency and user attitudes. Cluster analysis identified three distinct segments: enthusiasts, passive supporters, and sceptics. The findings confirm the ambivalent and heterogeneous nature of attitudes toward AI.

Implications for theory and practice:
The study contributes to the literature by integrating behavioral, attitudinal, and segmentation perspectives on AI use among digital generation representatives. From a managerial standpoint, the results highlight the need for differentiated AI implementation strategies, development of digital competencies, and consideration of the emotional dimension of human–AI interaction.