This study explored factors influencing ChatGPT adoption among higher education students in five Nordic countries (Sweden, Finland, Denmark, Norway, and Iceland) and the USA. The unified theory of acceptance and use of technology 2 (UTAUT2) framework was employed and extended to incorporate personal innovativeness. Data was collected from 586 students recruited through Prolific and analyzed using partial least squares structural equation modeling (PLS-SEM). The findings revealed varying patterns of relationships between different factors and behavioral intention in each region. In the Nordic countries, performance expectancy, hedonic motivation, and habit demonstrated positive relationships with behavioral intention. In the USA, the results revealed positive relationships between behavioral intention and performance expectancy, social influence, habit, and personal innovativeness. Performance expectancy emerged as the strongest predictor of behavioral intention in both regions. In both the Nordic countries and the USA, habit and behavioral intention emerged as the only predictors of ChatGPT use behavior. Behavioral intention demonstrated a marginally stronger influence on use behavior in both regions. These findings offer insights for educators and policymakers regarding AI integration in academic settings by highlighting common drivers and differences in AI adoption patterns.