Home sharing has become a buzzword in recent decades. Although revenue is increasing year by year, the home-sharing industry still faces fierce competition, not only from the traditional hospitality industry but also from OTA (online travel agency) platforms and other house-sharing platforms. To survive in this competitive accommodation market, a growing number of organizations have begun to focus on improving customer experiences through cultivating customer engagement and loyalty, thereby obtaining and sustaining competitive advantage. On the other hand, AI techniques are also widely used in the sharing economy to enhance personalization, analyse data, and increase output. However, despite the importance of positive customer experience to home-sharing platforms, and the potential usage of AI as a service, there are specific gaps in the existing literature. Firstly, there is a lack of theoretical foundation to support the relationship between AI and customer experience. Secondly, the literature on how AI is utilized in the sharing economy remains to be consolidated. Finally, minimal studies exist which examine if and how AI can be adopted to enhance the customer experience in the home-sharing industry, improve customer loyalty, and gain competitive advantage. This thesis uses qualitative and quantitative research methods to address the research gaps. The first phase of this study includes content analysis and systematic quantitative literature review to identify the relationship between AI and the customer experience in service, and how AI is used in the sharing economy. The systematic quantitative literature review is significant in this period as it clarifies the research gap that leads to the empirical research in the second phase. The empirical investigation examines guests who have used home-sharing platforms regarding their experience with AI, as well as levels of trust, engagement and loyalty towards the platforms and hosts. Online surveys and structural equation models are used in the second phase. [...]