Sustainability Meets Sensation: How Employee Sustainability and AI Interaction Shape Employee Happiness

Abstract

In the current volatile, uncertain, complex, and ambiguous technological landscape, the manufacturing sector of emerging economies faces critical challenges such as employee disengagement, escalating stress levels, and high attrition rates. While artificial intelligence (AI) is increasingly integrated into workplace processes, limited research examines AI sensation, employee sustainability, and its impact on employees’ emotional response. Addressing this gap, the present examines the impact of AI-integrated employee sustainability on employee happiness, contributing to Sustainable Development Goals. Adopting a mixed-method design, the research integrates qualitative and quantitative approaches. In the qualitative phase, expert insights from academicians & manufacturing sector employees are analyzed using Interpretive Structural Modeling and Cross-Impact Matrix Multiplication Applied to Classification, to map the relationships among key factors and assess their influence-dependence dynamics. Grounded in the theory of constructed emotion and qualitative findings, a comprehensive conceptual model is developed to explore the role of AI sensations & ES in shaping employees’ emotional responses. The second quantitative phase involves a structured survey administered to employees from multiple manufacturing organizations of emerging economies. Data is analyzed using confirmatory factor analysis for measurement models’ robustness, followed by structural equation modeling in SmartPLS software for testing hypothesized relationships. Results indicate that employee sustainability significantly drives employees’ positive emotions, while both AI sensation & AI empathy significantly and positively influence employees’ happiness.