Measuring AI Literacy of Future Knowledge Workers : A Mediated Model of AI Experience and AI Knowledge

Titelangaben

Hönigsberg, Sarah ; Mallek, Sabrine ; Watkowski, Laura Marie-Luise ; Weritz, Pauline:
Measuring AI Literacy of Future Knowledge Workers : A Mediated Model of AI Experience and AI Knowledge.
In: Proceedings of the 20th International Conference on Wirtschaftsinformatik (WI). - Münster, Germany , 2025

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Abstract

AI Literacy is crucial for knowledge workers, yet existing models fail to capture theoretical and practical evolvement and its predictors. This study extends the AI Literacy framework by Pinski and Benlian (2023), conceptualizing AI Knowledge as a second-order construct and using this as a mediator linking AI Experience and AI Literacy. Using Experiential Learning and Information Processing Theory, we examine AI Experience (Usage and Design) and its impact on AI Literacy via PLS-SEM. A survey of 352 master's students at a French business school reveals that AI Knowledge mediates the relationship between AI Experience and AI Literacy, challenging prior models. We contribute to IS by developing a new mediation model, extending the existing AI Literacy framework, and testing this in a new context. These results highlight the practical importance of hands-on AI Experience and AI Knowledge to enhance AI Literacy.