AI exposure breadth moderates differences between age-defined generational cohorts in preference for artificial intelligence rather than a human

A growing body of research questions the assumption that younger generations have a stronger preference for using artificial intelligence (AI) than older generations. While prior studies highlight the role of experience, little is known about how age, AI exposure breadth, and preference for AI over a human (hereafter, AI preference) interact across domains with different levels of potential consequences. This study addresses this gap. Data were collected through a quota-based online survey of 1,075 adults in Poland (analytical sample of 912 respondents familiar with the term “AI”). The analysis revealed a weak negative correlation between age and AI exposure breadth (r(910) = − 0.144, p <.001). Among the age-defined generational cohorts, Generation Z (Gen Z) showed a stronger AI preference than Baby Boomers (BB) and Generation X (Gen X) in a few domains, although effect sizes were small. AI exposure breadth was not a significant predictor of AI preference for Gen Z, the reference cohort, but it moderated differences between age-defined generational cohorts, with the strongest interaction effect observed for BB (B = 0.52, SE = 0.12, p <.001). Overall, the association between AI exposure breadth and AI preference was stronger in lower-stakes domains (F(1, 904) = 34.32, p <.001). As AI exposure breadth increased, the gap in AI preference between lower- and higher-stakes domains became more pronounced in Gen Z, Gen Y, and Gen X, but remained comparatively stable among Baby Boomers. These findings suggest that differences in AI preference were not uniform across age-defined generational cohorts and varied according to AI exposure breadth and different levels of potential consequences.