In the current modern age, Artificial intelligence (AI) chatbots becomes an important part for online shopping through providing a prompt response to the customers. Along with this increasing expansion, there are still limited studies available especially with respect to customer brand relationship. Therefore, this research aimed to explore the AI chatbots application as an e-service agents (interaction, perceived enjoyment, customization, and problem-solving capabilities) and their impact on customer brand relationship through increasing positive attitude of customers. For this purpose, this study also employs the Technology Acceptance Model (TAM) two indicators perceive ease of use and perceived usefulness to clarify how the distinct characteristics of chatbots influence customer-brand relationships. For this purpose, studies data were collected from the extant published papers from both of theoretical and empirical perspectives. Using the A-B-C model, which includes cognitive (thinking), affective (feeling), and behavioral (doing) components, the conceptual model examines various external factors namely interaction, perceived enjoyment, customization, and problem-solving capabilities have positive and significant relationship with perceived ease of use, perceived usefulness, attitude and customer brand relationship. Perceived usefulness and perceived ease of use also have significant relationship with attitude and customer brand relationship. The study also identifies the affective component of attitude as a key predictor of customer-brand relationship outcomes. Study with this relationship, contributes significantly to theoretical frameworks and offers valuable managerial insights. It emphasizes the importance of incorporating personalization into e-service agent marketing strategies and the critical role of affective attitudes in establishing emotional connections with customers through chatbot interactions. The paper provides significant managerial implications for businesses to improve customer brand relationship through improving strategic planning by incorporating affective attitudes in AI chatbots.