In the contemporary business environment, organizations increasingly focus on building strong, long-term customer relationships to maintain competitiveness. Traditional Customer Relationship Management (CRM) systems have served as essential tools to manage customer interactions, streamline sales processes, and enhance satisfaction. However, these conventional systems, reliant on manual processes and historical data, often fall short in delivering real-time insights, personalized experiences, and predictive decision-making capabilities. The rapid advancement of Artificial Intelligence (AI) has revolutionized CRM by integrating technologies such as machine learning, predictive analytics, natural language processing, and intelligent automation. AI-powered CRM systems enable organizations to analyze vast volumes of structured and unstructured data, predict customer behavior, and recommend optimal strategies, thereby enhancing operational efficiency and decision accuracy.

This study aims to examine the transformative role of AI in traditional CRM practices and its impact on customer experience, satisfaction, and organizational performance. Using a descriptive and analytical research design, primary data were collected from 150 respondents, including CRM managers, marketing professionals, and customer service executives, through structured questionnaires. Secondary data were sourced from journals, books, and industry reports. Data were analyzed using descriptive statistics, mean, and standard deviation to assess perceptions, adoption patterns, and benefits of AI-enabled CRM systems.