Factors that Affect Customer Trust with Intent Using Veronika's Generative-Based Chatbot on Providers Telecommunications

Abstract

The rapid development of generative artificial intelligence (AI) has transformed customer service interactions, including Telkomsel’s implementation of the Veronika chatbot as a digital service solution. However, maintaining customer trust and continued usage intention remains challenging because of variations in information accuracy, usability, and perceived benefits. This study examines the effects of chatbot information quality on perceived ease of use, perceived usefulness, customer trust, and continued usage intention toward Veronika, Telkomsel’s generative AI-based chatbot. This study employed a quantitative approach using partial least squares structural equation modeling (PLS-SEM). Data were collected from 397 Telkomsel customers who had interacted with the chatbot. The findings indicate that chatbot information quality significantly affects perceived ease of use and perceived usefulness, which, in turn, increase customer trust. Furthermore, trust plays a significant role in determining users’ intention to continue using Veronika. The results also demonstrate that perceived ease of use, perceived usefulness, and trust mediate the relationship between information quality and continued usage intention. These findings imply that improving the accuracy, relevance, and responsiveness of chatbot information, as well as the chatbot’s usability, is essential for strengthening customer trust and encouraging the sustained adoption of AI-based customer service platforms.