Augmenting human service agents with intelligent technologies

Abstract

Purpose This literature review examines how core intelligent technological capabilities, including artificial intelligence, machine learning, deep learning, and natural language processing, augment rather than replace service agents across the various stages and tasks of customer service interactions. Design/methodology/approach This study provides a systematic and cross-disciplinary review of empirical studies on applications of technology in human-to-human service interactions published over the last decade. The resulting 99 studies are analyzed using thematic mapping and interpreted through the lens of socio-technical systems theory and service-dominant logic. Findings The thematic mapping revealed six central themes on the integration of technology in human-to-human service interactions: (1) pre-service optimization, (2) interaction intelligence, (3) service agent well-being, (4) service agent monitoring, (5) emotion work and (6) collaborative service. These themes are organized into a conceptual framework that highlights key tensions and boundary conditions, forming the basis for a comprehensive future research agenda. Practical implications The findings underscore the importance of a human-centered approach, demonstrating how technology can enhance service agent roles, promote well-being, and enable collaboration in customer service. Originality/value The review shifts the focus from technology replacing service agents to technology augmenting their roles. It contributes new insights into how augmentation enhances service agent effectiveness, efficiency and well-being, offering a foundation for sustainable improvements in service interactions.