Extending the planned risk information seeking model (PRISM) in the context of artificial intelligence: from the perspective of individual differences

As artificial intelligence is increasingly being integrated into daily life, understanding the factors that drive individuals to seek AI-related information becomes more important. This study employs the Planned Risk Information Seeking Model as a theoretical framework to explore AI information-seeking behaviours from the perspective of individual differences. Apart from the effects of individual differences, the findings were generally in line with the theoretical model. However, negative affect negatively predicted information insufficiency and was not significantly related to information seeking intention. Furthermore, examination of the effects of individual differences revealed that I-type epistemic curiosity positively predicted both information insufficiency and information seeking intention, yet D-type epistemic curiosity was not significantly related to information insufficiency and information seeking intention. Moreover, information innovativeness was found to be negatively related to information insufficiency but positively related to information seeking intention. Theoretical and practical implications are discussed. © 2025 Informa UK Limited, trading as Taylor & Francis Group.