Open Access

Examination of intergenerational artificial intelligence attitudes of employees in hospitality enterprises: A mixed methods study

1 Tourism and Hotel Management Programme, Doğuş University, Istanbul, 34000, Türkiye ROR

Abstract

Artificial intelligence technologies are transforming operational processes in the hospitality sector and generating effects on employees’ perceptions, attitudes, and organizational adaptation dynamics. Within the digital transformation process, attitudes toward these technologies may vary across generational differences (Generation X, Y, and Z) as well as demographic variables such as gender, education, and income. This study aims to examine employees’ attitudes toward artificial intelligence in hospitality establishments by centering generational differences (Generation X, Y, and Z) and analyzing them in relation to other demographic variables. A mixed-methods research design was adopted. Quantitative data were collected through a survey administered to 446 employees working in hospitality enterprises operating in the Kuşadası destination. Qualitative data were obtained through open-ended questions directed to a total of 30 participants representing Generations X, Y, and Z. The quantitative findings indicate that attitudes toward artificial intelligence do not differ significantly across generations or basic demographic variables. However, qualitative results reveal notable generational differences in perceptions, expectations, and concerns, highlighting trust, perceived control, and human interaction as key differentiating factors. The study emphasizes that the success of artificial intelligence applications in the tourism sector depends not only on technical competence but also on human-centered design and generation-sensitive adaptation strategies.

Keywords

How to Cite

Yilmaz, C. (2026). Examination of intergenerational artificial intelligence attitudes of employees in hospitality enterprises: A mixed methods study. International Journal of Eurasia Social Sciences, 17(64), 615–631. https://doi.org/10.70736/ijoess.2213

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