Integrating the E-SERVQUAL Model with AI-driven Chatbots in Insurance Services to Enhance Millennial Satisfaction in Malaysia: PLS-SEM Approach

The shift in consumer expectations and technological advancements have significantly contributed to the digitisation of the Malaysian insurance sector. Designed to increase responsiveness, availability, and personalisation in consumer engagement, artificial intelligence (AI)-driven chatbots are a key component of this digital transition. Nonetheless, the wide adoption of these chatbots is hampered by a lack of trust. Customers remain sceptical about the chatbots’ ability to deliver precise, dependable, and secure guidance, particularly in the insurance sector. Such scepticism is exacerbated by the lack of comprehension of AI chatbots’ capabilities and benefits, their perceived inferiority to human agents, and the heterogeneous population in Malaysia, where in-person contacts are preferred for financial decisions that require privacy and confidentiality. This study aims to examine the E-SERVQUAL model in relation to AI-driven chatbot functionalities to assess their impact on service quality and customer satisfaction in insurance services. Notably, 200 millennial participants would be purposively sampled to gather and analyse data using partial least squares structural equation modelling (PLS-SEM). The current work could provide theoretical and practical insights into increasing customer interaction and service delivery via chatbots to reconcile customer expectations with AI technology in the insurance sector. Identifying the key determinants of chatbot adoption potentially enhances service quality and fosters trust in AI chatbots within local insurance businesses.