AI-powered chatbots for improving interactive user experience: state-of-the-art

Zhou, Ti, Liu, Ying ORCID: https://orcid.org/0000-0001-9319-5940 and Kumar, Maneesh ORCID: https://orcid.org/0000-0002-2469-1382 2024. AI-powered chatbots for improving interactive user experience: state-of-the-art. Presented at: The 51st International Conference on Computers and Industrial Engineering (CIE51), Sydney, Australia, 9-11 December 2024. Proceedings 51st International Conference on Computers & Industrial Engineering (CIE51). New York, USA: Computers & Industrial Engineering, pp. 137-149.

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Abstract

Recent advancements in chatbot technology, driven by Natural Language Processing (NLP) and machine learning techniques, have led to the widespread adoption of Artificial Intelligence (AI) chatbots across various sectors. These AI chatbots are designed to enhance user and customer experience by providing customized services. While existing literature on chatbots normally covers technical aspects, impact, and applications across disciplines, there is limited research from the perspective of users and customers that focuses on user experience (UX) improvement during the interaction process. To offer a more thorough analysis of the interactive user experience between users and AI chatbots, this paper reviews relevant studies from databases Scopus, Web of Science, and IEEE over the past decade. The review highlights the significance of user-centred design for AI chatbots, identifying key factors influencing UX from pragmatic and hedonic quality. It points out how AI technology empowers chatbots to deliver tailored and personalized services to enhance UX. Moreover, the review reveals that current methods for evaluating UX with AI chatbots lack objectivity and comprehensiveness, emphasizing the necessity of establishing evaluation frameworks and standardized metrics for effective cross-system comparison. Finally, the review outlines future research directions for academic exploration of AI-powered chatbots and UX.

Item Type:	Conference or Workshop Item - published (Paper)
Status:	Published
Schools:	Schools > Engineering
Publisher:	Computers & Industrial Engineering
ISBN:	9798331316259
Last Modified:	13 Mar 2026 02:30
URI:	https://orca.cardiff.ac.uk/id/eprint/171545

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