The rapid digitalization of customer service has led to an increased use of artificial intelligence, particularly AI-driven chatbots, within the retail industry. These chatbots are widely used to enhance service efficiency, provide instant support, and reduce operational costs. At the same time, their growing presence raises questions about how they affect customer experience and long-term customer loyalty. The purpose of this study is to examine how AI-driven chatbots influence customer experience and customer loyalty within the retail sector. The study focuses on consumers’ perceptions of chatbot interactions and how these perceptions affect trust, repurchase intention and brand attitude. A quantitative research approach was applied using a survey targeting consumers with prior experience of AI-driven chatbots, with a minor focus on the Swedish retailers Elgiganten and Power. The theoretical framework is based on the Technology Acceptance Model (TAM), Customer Loyalty Theory, as well as the Stereotype Content Model (SCM) and Social Presence Theory. These theories enable an analysis of both technological and emotional aspects of chatbot interactions. In total, 104 valid responses were analyzed. The results indicate that AI-driven chatbots are generally perceived as useful and efficient, particularly in terms of accessibility and speed of service. Positive perceptions of chatbot competence and usability contribute to higher customer satisfaction and increased trust in the brand. However, the findings also reveal that a lack of empathy and limitations in handling complex issues may negatively affect the customer experience. The study suggests that chatbots can enhance customer loyalty when they are perceived as reliable, competent and safe, but that human customer service remains important for building emotional connections. In conclusion, AI-driven chatbots are not sufficient enough to strengthen customer experience and customer loyalty in the retail industry, provided that they successfully balance technological efficiency with elements of human interaction.