DOI - Mendel University Press

DOI identifiers

DOI: 10.11118/ecos2026_017

GENERATION Z AND AI-DRIVEN SHOPPING: COMPARING ONLINE AND IN-STORE CONSUMER EXPERIENCES

Benjamin Křištof1, Jana Dannhoferová2
1 Faculty of Business and Economics, Mendel University in Brno, Zemědělská 1, 613 00 Brno, Czech Republic
2 Department of Informatics, Faculty of Business and Economics, Mendel University in Brno, Zemědělská 1, 613 00 Brno, Czech Republic

This paper examines the methods and intensity of Artificial Intelligence (AI) tool utilization by Generation Z within online and offline shopping environments. The empirical investigation employs a mixed-methods research design, combining a quantitative questionnaire survey (n = 114) and six semi-structured interviews conducted in April and May 2026 among respondents aged 18–27 in the Czech Republic. The objective was to identify dominant AI tools, key motivators, and barriers to their adoption, and to evaluate consumers‘ willingness to share personal data in both environments. Online interaction with AI is more conscious, focusing primarily on generative assistants (ChatGPT), visual search, and recommendation systems. In stores, self-checkout counters and interactive kiosks dominate, though their utilization is often unreflected by consumers. Statistical testing of five hypotheses revealed a higher willingness to share personal data in the online environment (p = 0.018). Surprisingly, however, it also demonstrated statistically significantly lower privacy concerns in the offline environment compared to online (p < 0.001), which contradicts the assumption derived from the literature. No gender differences in the frequency of AI usage were detected. Based on these findings, a “phygital” strategy was formulated, linking a unified customer data identity, the smartphone as a mediator between environments, and the principles of Explainable AI (XAI).

Keywords: Generation Z; artificial intelligence (AI); online shopping; in-store shopping; phygital retail; mixed-methods research; consumer behavior; privacy paradox

pages: 176-185, online: 2026



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