Sarcouncil Journal of Engineering and Computer Sciences

Abstract: Emotional AI represents a transformative advancement in customer experience personalization, leveraging technologies that detect and respond to human emotions through facial expressions, voice tonality, linguistic patterns, and multimodal integration. This article explores how emotional AI transcends traditional personalization by incorporating affective computing into customer interactions, creating more intuitive and responsive experiences. It examines the technological foundations underpinning these systems, including computer vision approaches to facial expression analysis, speech emotion recognition, natural language processing for sentiment detection, and machine learning architectures optimized for emotional intelligence. Applications across various customer touchpoints—from emotionally responsive chatbots to dynamic call routing based on emotional states—demonstrate significant potential for transforming service delivery. The article addresses critical challenges, including cross-cultural variations in emotional expression, privacy concerns, manipulation risks, accuracy limitations, and evolving regulatory requirements. It concludes by exploring future directions for emotional AI integration with broader personalization ecosystems, its impact on satisfaction metrics, evolving business models, research frontiers, and long-term societal implications of emotionally aware technology in reshaping customer-business relationships.