<![CDATA[This study examines the impact of implementing generative AI voice chatbots on customer expectations and satisfaction in the banking sectors of Kazakhstan, Russia, and Italy. To achieve this objective, this study conducted a survey of 253 customers from 35 commercial banks in Kazakhstan, Russia, and Italy from November 2023 to early April 2024. This study employed partial least squares structural equation modelling (PLS-SEM) to assess and validate the validity and reliability of the research model. The study integrates the Expectation Confirmation Model with AI components to analyze factors influencing customer satisfaction with AI-enabled digital banking services. Key findings indicate that expectation confirmation, perceived performance, visual attractiveness, problem-solving capabilities, and communication quality significantly affect customer satisfaction with AI chatbots. However, trendiness and customization features showed minimal impact. The research also explores how customer satisfaction and corporate reputation influence chatbot adoption. Additionally, the study investigates the relationship between chatbot adoption and productivity performance in banking operations. The study provides several policy recommendations, including enhancing perceived performance, expectation confirmation, communication quality, visual attractiveness, and corporate reputation, which can improve customer satisfaction and increase confidence in generative AI voice chatbots in the digital banking industry. Doi: 10.28991/ESJ-2024-08-06-09 Full Text: PDF]]>
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