With industries becoming hyper-personalized and data-driven, the “Customer Relationship Management (CRM) systems are also undergoing a paradigm shift encompassing the realization of Artificial Intelligence (AI)” and predictive analytics. The given paper discusses the way AI-enhanced CRM systems help companies evolve beyond transactional and transient customer treatment to a more actionable and insight-based customer-based interaction process. Through machine learning, natural language processing, and behavioral analytics, contemporary CRMs are capable of predicting how customers will act, tailoring engagements to their personal preferences, streamlining the sales pipeline and minimizing churn. This paper will examine the effect of augmented CRM platforms using AI on the satisfaction, retention, and efficiency of customers by using the recent case studies of industries like retail, finance, and healthcare. It also looks at the ethical and technological issues that surround the use of predictive algorithms such as data privacy issues, model transparency, and integration problems. Based on a secondary qualitative methodology and thematic analysis, this paper summarizes the main trends and insights to provide an organized plan of action of any organization that seeks to implement or improve AI-based CRM strategies. The evidence indicates that ethically and strategically applied AI in CRM turns into the central generator of competitive advantage and long-term customer engagement.