Firms are turning more and more to artificial intelligence (AI) to adapt offers, content and service exchanges to each individual customer. Shoppers now expect this level of tailoring, but recent surveys point to weakening confidence in how companies handle data and AI. The present paper asks how AI-driven personalization shapes customer trust, satisfaction and loyalty. Drawing on a structured review of peer-reviewed research together with recent industry and regulatory material (McKinsey, Salesforce, Cisco and India's Digital Personal Data Protection framework), it builds a conceptual model containing seven propositions. The model holds that personalization reaches trust by two opposing paths: perceived relevance, which builds trust, and perceived privacy vulnerability, which erodes it. Reported statistics indicate that over 70% of consumers anticipate personalized interactions and roughly three in four are frustrated when they do not get them. Meanwhile, across Salesforce's successive studies, the proportion trusting companies to apply AI ethically dropped from 58% to 42%, while the proportion feeling they are treated as individuals climbed from 39% to 73%. Experimental and field findings suggest that the impact of personalization hinges on existing trust and on how openly data are gathered. The paper concludes that personalization lifts satisfaction and loyalty only if it is delivered through a design that protects trust, and it supplies a managerial framework, measurement scales and an agenda for primary research in India