What drives adoption of artificial intelligence across generations? The role of perceived usefulness,effort expectancy,digital literacy,social influence,and trust in privacy

Abstract

Background: Artificial intelligence (AI) has become a central driver of technological, organizational, and social change. Despite its widespread adoption, empirical evidence shows that adoption patterns vary significantly across generational cohorts. Objective: This study examines how perceived usefulness, effort expectancy, digital literacy, social influence, and trust in privacy relate to intentions to use AI technologies among Generation Z, Generation Y, and Generation X. Grounded in the Unified Theory of Acceptance and Use of Technology (UTAUT) and its extensions, the study employs a quantitative survey design (N = 206), conducting correlational and multivariate regression analyses separately for each generational group. Results: The results indicate that effort expectancy is a strong predictor across all generations, while perceived usefulness, digital literacy, and social influence have distinct effects by generation. Contrary to common assumptions, trust in privacy does not significantly predict intention to use AI across cohorts. Conclusions: The findings indicate that AI adoption is a multidimensional and age-dependent process. These generational differences highlight the need for age-sensitive AI design and implementation strategies, to promote equitable and informed use.