AI Chatbots in Customer Service: Do they Truly Enhance Customer Satisfaction?

Abstract

The use of artificial intelligence (AI) in digital marketing and customer service is growing in importance, AI chatbots have emerged as a key tool shaping user experiences and strengthening brand customer relationships. This research integrates the Information System Success Model (ISSM) with consumers' perceived value dimensions such as perceived trust, experiential value, functional value, and social value to investigate the factors that influence brand love in the context of AI chatbot engagements. 314 respondents provided information via an online survey, and Partial Least Squares Structural Equation Modeling (PLS-SEM) was applied to the analysis. The results show that perceived values and trust are strongly impacted by system, information, and service quality, all of which increase brand love. Among these factors, system quality exerts the strongest impact, underscoring the importance of technical reliability, ease of use, and responsiveness in shaping user trust and positive interaction experiences. Conversely, perceived trust does not directly predict Brand Love, suggesting that trust in chatbots alone is insufficient to generate emotional attachment without meaningful experiential and functional engagement. Meanwhile, social value demonstrates a crucial role in fostering Brand Love by enhancing users’ sense of connection, understanding, and autonomy during chatbot interactions. From a theoretical standpoint, this study extends the ISSM framework by incorporating emotional and value-based constructs, offering a deeper understanding of how Brand Love develops within AI-driven digital service environments. Practically, the results offer useful recommendations for companies and developers, highlighting the necessity of combine strong technical performance with emotionally engaging and personalized design to strengthen long-term brand relationships in the era of digital transformation.