Factors driving organizational members’ continuance intention for use of generative artificial intelligence

It is important both academically and practically to understand the factors predicting organizational members’ continuance intention for use of generative artificial intelligence (GenAI). We incorporated privacy concerns and self-efficacy into an expectation–confirmation model of GenAI usage continuance intention, and tested this model using partial least squares analysis with data from 172 members of organizations who had experience using GenAI. The results showed that user satisfaction was not significantly associated with continuance intention, while perceived usefulness was a significant predictor of continuance intention, and perceived enjoyment was significantly associated with user satisfaction. These results indicated that privacy concerns played an important role in reducing perceived usefulness. Finally, self-efficacy played a role in the decision of whether to continue using GenAI. With regard to successful adoption and leverage of GenAI, our findings offer insights for companies aiming to establish operational strategies and information protection policies.