Consumer Perceptions of AI-driven Chatbots in Digital Platforms : Factors Affecting Service Quality and Satisfaction

Abstract

In the digital age, artificial intelligence (AI) has become a significant part of how customers interact with online store assistants and customer service. Despite AI chatbots' impact on service delivery speed, cost efficiency, and around-the-clock customer support, the impact on customer satisfaction and service quality remains poorly comprehended. This thesis uses hybrid quantitative and qualitative methods to answer the research question on drivers and factors affecting perceived service quality and satisfaction. Additionally, providing insights for managerial considerations for the future development of AI chatbots. This thesis found that the results are in line with previous research on models TAM, UTAUT and SERVIQUAL. Con-cluding that performance, ease of use and reliability are correlated and in causal relation with the perceived satisfaction and service quality. Enhancing capabilities in these areas would positively affect the experienced satisfaction and service quality. Current overall im-pressions and attitudes towards AI chatbots are critical, and most customers would rather speak with a human customer service agent. Yet, there is an indication of better applications in the future. The issues, especially with the performance, should be addressed to provide accurate, fast and valuable information for the customer. Currently, the performance is per-ceived as lacking when it comes to more complex problem-solving and understanding. The AI chatbots should be able to actually solve customers' problems. Otherwise, they will have to seek human assistance. Future development, especially in generative artificial intelligence, could be seen as an opportunity for businesses to solve more complex customer problems with precision and speed, leading the better customer experience in digital platforms. In a complicated digital world, consumers appear to appreciate the ease of use in AI chatbots, advising businesses to focus on customer-centric design and UX/UI of the chatbots. Reliability and trust in a company's compliance with ethical operating models and data privacy also affect the experience with the service provider. This research proposes further future re-search into factors that affect the perceived service quality. The suggestion is to focus on anthropomorphism and personalisation of AI chatbots since there can be found factors to better identify since this research did not manage to find consistent data on the issue.