Leader-Member Exchange, Responsible Artificial Intelligence, and Self-Determination Theory: An Integrative Review of Leadership, Autonomy, and Motivation in Ai-Augmented Workplaces

A bstract This review examines how leader-member exchange (LMX) quality, responsible artificial intelligence (AI) practices, and self-determination theory (SDT) jointly shape employee experiences in workplaces increasingly influenced by algorithmic management. Drawing on recent scholarship, we argue that digital performance dashboards and monitoring systems may restrict workers’ autonomy and relatedness, thereby inducing stress and reducing engagement. In contrast, high-quality LMX relationships offer socioemotional support and foster intrinsic motivation. SDT further emphasizes that fulfilling the basic psychological needs of autonomy, competence, and relatedness enhances engagement and well-being. Because most studies examine these constructs in isolation, this synthesis integrates leadership and technology research while also considering generational differences. Through this integration, we propose a conceptual framework linking AI practices, LMX quality, psychological safety, and need satisfaction, and we identify directions for future research and practice.