<p>The adoption of AI-powered services in customer service is critical for organizational efficiency, yet consumer resistance remains a significant hurdle. While existing research has identified key barriers, the complex interrelationships between them are not well understood. This study identifies ten critical barriers namely Perceived Data Privacy Risk, Algorithmic Distrust, Perceived Lack of Transparency, Perceived Creepiness, Perceived Loss of Social Interaction, Lack of Human Touch, Perceived Usefulness, Perceived Ease of Use, Technology Anxiety, and Status Quo Bias. It employs Fuzzy Total Interpretive Structural Modelling (Fuzzy TISM) to structure these barriers into a hierarchical model interpreting the directional links. The barriers are categorized by MICMAC analysis according to their driving and dependence power. The results show that the two most basic and significant obstacles are perceived data privacy risk and algorithmic distrust, lack of human touch and perceived loss of social interaction are identified as high-dependent outcome-level barriers. The study concludes that unless the fundamental problems of trust and data privacy are thoroughly addressed, first managerial efforts aimed only at promoting usefulness and ease of use will be ineffective. This research provides a validated strategic roadmap for practitioners and contributes a novel hierarchical model to the theoretical discourse on technology adoption.</p>