Technostress and Employee Performance in AI-Enabled and Hybrid Work Contexts: A Systematic Literature Review

Abstract

The rapid integration of Artificial Intelligence (AI) and the expansion of hybrid work arrangements have transformed the modern workplace, while simultaneously exposing employees to increasing technological demands and potential sources of technostress. This study investigates how technostress shapes employee performance within the dual context of AI adoption and hybrid work arrangements, employing a systematic literature review methodology. Sixteen empirical articles published between 2020 and 2026, drawn from well-regarded academic databases, form the basis of this synthesis. The analysis reveals that technostress operates as a dualistic construct, capable of both undermining and facilitating employee performance. When functioning as a hindrance stressor, technostress amplifies burnout, heightens anxiety, and diminishes performance outcomes. However, when employees interpret it as a challenge stressor, technostress may stimulate engagement, encourage creative behavior, and strengthen digital adaptability. Key antecedents are identified across technological, organizational, and individual dimensions. Mediating variables, particularly work engagement and burnout, alongside moderating conditions such as perceived organizational support and digital literacy, prove pivotal in determining the direction and magnitude of this relationship. The evidence indicates that the consequences of technostress are highly context-sensitive, varying according to how individuals appraise the stressor and the degree of support available within their organizations.