MECHANISMS BY WHICH AI-ENABLED CRM SYSTEMS INFLUENCE CUSTOMER RETENTION AND OVERALL BUSINESS PERFORMANCE: A SYSTEMATIC LITERATURE REVIEW OF EMPIRICAL FINDINGS

Abstract

This systematic literature review examined the mechanisms through which Artificial Intelligence–enabled Customer Relationship Management (AI-CRM) systems influence customer retention and overall business performance across diverse industrial contexts. A total of 72 empirical studies published between 2018 and 2022 were systematically analyzed to identify the quantitative pathways, mediating constructs, and moderating factors that explain AI’s impact on organizational and relational outcomes. The reviewed literature revealed that AI-CRM systems enhance performance through four primary mechanisms: data-driven personalization, cognitive automation, predictive and prescriptive analytics, and experience-based sentiment intelligence. These mechanisms collectively strengthen customer engagement, satisfaction, and loyalty while improving operational efficiency, decision-making accuracy, and profitability.The findings demonstrated that AI integration within CRM platforms produces significant positive effects on both financial and non-financial outcomes by transforming static data into actionable insights and adaptive customer interactions. Customer retention consistently emerged as the key mediating variable linking AI adoption intensity to profitability, confirming that technological sophistication translates into performance benefits primarily through long-term relational continuity. Moreover, firm size, digital readiness, and data governance maturity were identified as significant moderators that influenced the strength of AI’s impact, indicating that organizational context shapes the effectiveness of AI-CRM strategies.Across sectors such as banking, retail, telecommunications, and hospitality, evidence showed that predictive modeling and automation improved response times, reduced churn, and optimized marketing resource allocation. Personalization mechanisms were particularly influential in customer-facing industries, while cognitive automation drove process efficiency in service-intensive sectors. The synthesis highlights that AI-enabled CRM is not merely a technological enhancement but a strategic transformation capability that integrates analytics, automation, and customer experience intelligence into a unified framework for sustained competitive advantage. This review contributes to the growing empirical foundation of AI-CRM research by offering a comprehensive, evidence-based understanding of how artificial intelligence reshapes customer management and business performance outcomes.