Impact of AI Chatbots on Consumer Service Experience and Perceived Accountability of Firms

DOI

10.2991/978-2-38476-547-8_13How to use a DOI?

Keywords

AI ChatBots; Service quality; Perceived Accuracy; Accountability Expectation; Consumer Satisfaction; Consumer Loyalty

Abstract

With the high adoption rate of AI-powered chatbots in the customer-facing services, the algorithm has reshaped how consumers evaluate the quality of services, accuracy, and responsibility of the firms in the digital contact points. Though chatbots are said to be efficient, fast-paced, and available 24/7, the issue of the utilization of chatbots by consumers is whether they will assist in maximizing satisfaction and loyalty. This paper explores how the quality of chatbot services affects perceived accuracy, consumer satisfaction, as well as consumer loyalty and how the expectations of accountability influence the development of these associations. Based on the service quality theory, the expectation confirmation theory, and the emerging literature on AI accountability, this conceptual model could be developed to remind that both the cognitive (perceived accuracy) and affective (satisfaction) pathways contribute to the impact of the chatbot interactions on the loyalty outcome. The survey was a quantitative study based on a survey, and 393 valid responses were gathered by employing a survey-based approach of the students in the fields of higher education in Gujarat and Maharashtra who had used chatbots in the banking, e-commerce, or telecommunication sector within the last 30 days only. The measurement model had high reliability, convergent, and discriminant validation in using SmartPLS 4. Structural equation modeling showed that the quality of the chatbot service is a significant factor of perceived accuracy, which in its turn is a strong predictor of satisfaction and loyalty. Satisfaction has also proved to be a major factor in customer loyalty, which validates its leading position in customer experience models. Importantly, the direct impact of the quality of the services on the level of satisfaction was not significant, which suggests that the quality of the chatbots is rated by the users using cognitive evaluations in terms of accuracy instead of direct emotional evaluations. The influence of the accountability expectation was noteworthy on the perceived accuracy, as well as the satisfaction, indicating that when users expect the firms to be responsible in cases of errors of chatbots, the perception of chatbot interactions becomes more critical but valuable. The results indicate the critical significance of the perceived accuracy and accountability in determining consumer experience in service environments mediated by AI. The theoretical contribution of the study is that by involving accountability expectations in chatbot service models, the control of the mediating role played by accuracy becomes clear. In practice, the findings provide practical knowledge that firms should apply to better the chatbot design, transparency, and redress instruments to ensure satisfaction and loyalty in an ever-growing-automated service ecosystem.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Sachin Deshmukh
AU  - Anil Sharma
PY  - 2026
DA  - 2026/03/05
TI  - Impact of AI Chatbots on Consumer Service Experience and Perceived Accountability of Firms
BT  - Proceedings of the International Conference on Socio Legal Intricacies of Artificial Intelligence (ICSLIAI 2026)
PB  - Atlantis Press
SP  - 107
EP  - 117
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-547-8_13
DO  - 10.2991/978-2-38476-547-8_13
ID  - Deshmukh2026
ER  -