INTEGRATING EMOTION AI IN HR DECISION-MAKING FOR EMPLOYEE WELL-BEING AND PERFORMANCE - Wui San Taslim; Vivi Vivi (Published by the Faculty of Economics and Business, University of Labuhanbatu, North Sumat, 2026)
PURPOSE - This study examines how Emotion Artificial Intelligence (Emotion AI) influences the quality of Human Resource (HR) decision-making through the mediating role of Emotionally Aware AI Decision Making (EA-AIDM). EA-AIDM is introduced as a socio-technical construct that reflects AI systems, capacity to detect, interpret, and respond to human emotions in HR contexts.METHODOLOGY - Using a quantitative design, the study applied Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyze responses from 122 HR professionals representing technology, manufacturing, and financial sectors. Participants were selected through purposive and stratified sampling, with inclusion criteria such as managerial roles and experience using AI-driven HR systems. Analyses included reliability, validity, factor loadings, and mediation testing.FINDING - Results reveal that AI adoption has no direct impact on HR decision-making (β = 0.178, p = 0.085) but exerts a significant indirect influence through EA-AIDM (β = 0.364, p < 0.001), indicating partial mediation. Among EA-AIDM indicators, context awareness and risk aversion showed the strongest effects, while emotion detection was weakest (mean = 2.69). These findings underscore the importance of designing emotionally aware AI that balances analytical precision with empathy to achieve ethical and effective HR decisions