AI governance and employee well-being in digital workplaces: A systematic literature review

Abstract

The rapid expansion of AI-mediated workplaces has transformed digital work culture, reshaping how organizations manage, monitor, and evaluate employees. While AI-driven systems enhance operational efficiency and support data-driven governance, they also raise ethical concerns regarding surveillance, autonomy, fairness, and employee well-being. This study presents a Systematic Literature Review (SLR) using the PRISMA framework and thematic synthesis to identify and analyze 44 peer-reviewed articles published between 2015 and 2026 from six databases: Scopus, Web of Science, ScienceDirect, Emerald Insight, SpringerLink, and Google Scholar. The findings are organized into six themes: AI adoption in digital workplaces, employee trust in AI, ethical tensions in algorithmic decision- making, algorithmic management and workplace control, psychological well-being, and human-centered AI governance. The review shows that, despite improving organizational performance, AI-mediated systems contribute to technostress, burnout, AI anxiety, identity threats, and reduced worker autonomy. Key ethical concerns include algorithmic bias, opacity, discrimination, and inadequate institutional governance. This study contributes an integrative conceptual framework linking algorithmic workplace practices, ethical challenges, and employee well-being, moderated by organizational support, AI transparency, digital capability, and ethical leadership, alongside a practical framework for implementing sustainable, human-centered AI governance in digital workplaces.