EMOTION-AWARE AI-POWERED CRM SYSTEMS FOR HYPER-PERSONALIZED ENGAGEMENT IN OMNICHANNEL CUSTOMER JOURNEYS AND FEDERATED SENTIMENT INTELLIGENCE FRAMEWORK INTEGRATING REAL-TIME BEHAVIORAL ANALYTICS, PRIVACY-PRESERVING LEARNING, AND PREDICTIVE INTENT MODE

The rapid digital transformation of customer-facing industries has fueled the evolution of Customer Relationship Management (CRM) systems from static databases to intelligent engagement platforms. This paper proposes a novel architecture that integrates emotion-aware artificial intelligence (AI) into CRM systems, empowering hyper-personalized omnichannel customer journeys. Simultaneously, we introduce a Federated Sentiment Intelligence (FSI) framework that utilizes privacy-preserving federated learning, real-time behavioral analytics, and predictive intent modeling. By leveraging distributed machine learning and emotion recognition technologies, the system enhances adaptive personalization while safeguarding customer data. This research validates the effectiveness of federated learning in improving cross-channel sentiment interpretation, reducing false positives, and increasing customer engagement across decentralized environments.