Enhancing User Experience With a Generative AI Chatbot
Jeong Soo Kim, Minseong Kim, Tae Hyun Baek
Abstract
With the rapid evolution of artificial intelligence (AI), this study aims to examine the interplay among the perceived usability, perceived enjoyment, perceived responsiveness, and intention to continue using ChatGPT. Structural equation modeling (SEM) was used to investigate our proposed model. We recruited 446 ChatGPT users through an online survey conducted on the Connect platform, powered by CloudResearch. Perceived usability (β = 0.254) and enjoyment (β = 0.438) significantly influence satisfaction with ChatGPT. However, perceived responsiveness is not significantly related to perceived attachment or satisfaction. Furthermore, we established that perceived attachment (β = 0.405) and satisfaction (β = 0.447) are pivotal in shaping users’ intentions to continue using ChatGPT, providing insights into human–AI interactions. The practical implications of our findings suggest that generative AI chatbots should be crafted with a focus on enjoyable, user-centered interfaces that foster long-term user satisfaction and engagement. AI developers should design AI conversation flows and chatbot personas to optimize the user experience.