Artificial Intelligence Adoption, Workplace Stress, and Employee Well-Being in the Digital Commerce Era

Abstract

The rapid diffusion of artificial intelligence (AI) technologies across digital commerce including recommendation engines, chatbots, algorithmic scheduling, automated performance monitoring, and generative-AI copilots is reshaping how employees experience their work. While AI adoption promises efficiency, personalization, and competitive advantage for e-commerce and platform-based organizations, a growing body of evidence suggests it simultaneously introduces new sources of technostress, job insecurity, and psychological strain. This paper develops an integrated conceptual and methodological framework for examining the relationship between AI adoption, workplace stress, and employee well-being within digital commerce organizations. Drawing on the Job Demands-Resources (JD-R) model, Conservation of Resources (COR) theory, and the Technostress framework, the paper proposes a set of testable hypotheses linking AI adoption intensity to techno-stressors (techno-overload, techno-invasion, techno-uncertainty, techno-complexity, and techno-insecurity), and examines how organizational support, AI literacy, and self-efficacy moderate the stress–well-being relationship. A mixed-methods, cross-sectional survey design using Partial Least Squares Structural Equation Modeling (PLS-SEM) is proposed for empirical validation. The paper concludes with a discussion of managerial implications for human-centered AI implementation, study limitations, and directions for future longitudinal and cross-cultural research.

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