Exploring the Intersection of Big Data and AI With CRM Through Descriptive, Network, and Contextual Methods

As artificial intelligence (AI) continues to gain prominence, understanding its application in customer relationship management (CRM) has become increasingly critical. Advances in computing power, big data availability, AI methodologies, and the growing adoption of CRM systems have driven significant interest in AI-based CRM from both academia and industry. However, comprehensive reviews of this rapidly evolving domain remain limited. Using a systematic review approach, this study analyzes 840 documents from the Web of Science (WoS) database, following the PRISMA framework for study selection. Through descriptive, network, and contextual analyses, we identify key research clusters, including Enhancing Customer Experience with AI, predictive analytics in CRM, AI-CRM adoption and digital transformation, and Emerging AI Techniques in CRM. The findings highlight a significant shift toward AI-powered hyper-personalization, explainable AI, federated learning, and IoT-enhanced CRM. This study contributes by mapping the research landscape, uncovering emerging trends, and providing future research directions on the adoption and effectiveness of AI in CRM, AI ethics, the integration of IoT with AI in predictive CRM and AI-driven sentiment analysis, offering valuable insights for scholars and practitioners.