AI-induced privacy concerns: examining the moderating effect of AI fear on customer data sharing

Purpose This study explores the factors influencing customers’ willingness to disclose personal information (WDPI) in electronic banking (e-banking), with a focus on how fear of artificial intelligence (AI) moderates these relationships. Grounded in privacy calculus theory, the research model incorporates personalization, financial literacy, satisfaction and loyalty as key predictors of WDPI. Design/methodology/approach A survey was administered to 408 e-banking users in Portugal, and the data were analyzed using partial least squares structural equation modeling (PLS-SEM). Findings Results show that personalization and loyalty have a positive impact on WDPI, while financial literacy negatively affects it. Satisfaction indirectly influences WDPI through loyalty. Fear of AI moderates two key pathways: it diminishes the positive effect of personalization and amplifies the negative impact of financial literacy on WDPI. The model accounts for 36% of the variance in WDPI. Originality/value This study advances the understanding of information disclosure in digital banking by integrating cognitive (e.g. financial literacy and personalization) and emotional (e.g. fear of AI) dimensions. It highlights how psychological responses to AI shape customer behavior, offering novel insights for e-banking service personalization strategies and privacy management.