Artificial Intelligence and Employee Engagement: The Role of Managers in the Digital Workplace

Abstract

Artificial intelligence is reshaping how organizations coordinate work, allocate tasks, and supervise performance. Research on this shift has concentrated on productivity outcomes, leaving the behavioral consequences for employees and managers expected to absorb the disruption on their behalf underdeveloped. This paper advances a conceptual framework specifying how AI adoption reaches employee engagement through two opposing pathways. Integrating Self-Determination Theory with the Job Demands–Resources model, we argue that AI functions simultaneously as a job resource, supporting perceived competence and autonomy, and as a job demand, generating technostress through algorithmic control and surveillance. We propose that AI literacy and AI anxiety determine which pathway dominates. The framework’s distinctive contribution is a cross-level proposition: algorithmic coordination displaces core middle-management functions, producing role ambiguity that undermine managers’ capacity to supply the psychological safety their subordinates require. Managerial insecurity is therefore not peripheral to employee engagement but antecedent to it. We conclude with a PRISMA-based systematic review protocol through which the framework’s five propositions can be evaluated against the existing empirical record.

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