AI has rapidly become a key player in the Customer Service landscape, revolutionizing how companies interact with customers, deliver support, personalize experiences, and navigate customer interactions. The use of AI-driven chatbots, virtual assistants, recommendation systems, predictive analytics, and generative AI are driving the shift of traditional service provider roles into automated tasks. While the technologies offer great benefits in terms of responsiveness, availability, personalization, and operational efficiency, achieving the adoption of these technologies greatly relies on customer trust. Fears and concerns about privacy, security, fairness, wrong answers, lack of transparency, or no human involvement may prevent customers from engaging with AI. Thus, a trusted AI-driven customer service goes beyond just technical capabilities. This research identifies and forays into an empirical model to explore the effect of the trustworthy attributes of AI on consumer trust in AI-driven customer service. Transparency and explainability, fairness, privacy and data protection, reliability and robustness, security, human oversight, and accountability are the main elements of the proposed framework for trustworthy AI. These dimensions are recommended to be viewed as a higher-order construct that is perceived trustworthiness of AI that impacts customer trust. Perceived risk is included as an intervening variable and perceived customer control is a trust-enhancing complimentary factor. Customer trust is then suggested to affect customer satisfaction, continuance intention, and customer loyalty. The research design is quantitative research which is applied to the respondents who have previously contacted the customer-service systems based on artificial intelligence. The study is of quantitative research method with a structured questionnaire to the customers who have previously interacted with the customer-service systems based on artificial intelligence. Measurement and