Humanizing AI in Service Workplaces: Exploring Supervisor Support as a Moderator in HPWSs

Abstract

As artificial intelligence (AI) becomes increasingly embedded within service-oriented High-Performance Work Systems (HPWSs), understanding its implications for employee well-being and organizational sustainability is critical. This study examines the relationship between AI service quality and job satisfaction, considering the mediating effect of perceived organizational justice and the moderating influence of supervisor support. Drawing on the ISS model, equity, organizational justice, and Leader–Member Exchange (LMX) theory, data were collected from a diverse sample of service sector employees through a cross-sectional design. The findings indicate that higher AI service quality significantly enhances job satisfaction, particularly in environments with strong supervisor support. Contrary to expectations, perceived organizational justice did not mediate the AI-satisfaction link, suggesting that perceived organizational justice constructs may be less influential in AI-mediated contexts. Instead, supervisor support emerged as a key contextual enabler, strengthening employees’ positive perceptions and emotional responses to AI systems. These results emphasize that technological optimization alone is insufficient for building sustainable service workplaces. Effective leadership and human-centered practices remain essential to fostering trust, satisfaction, and long-term engagement in digitally transforming organizations. This study offers practical and theoretical insights into integrating AI and human resource strategies in support of socially sustainable service systems.

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