Harish Yadav, Rajib Lochan Dhar · Acta Psychologica 2026 · 2026
DOI: 10.1016/j.actpsy.2026.107841
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Employee AI awareness (AIA) has emerged as a critical yet conceptually diffuse construct capturing how employees cognitively and affectively interpret the implications of artificial intelligence (AI) for their work. Addressing calls for psychologically grounded research on AI in organizational contexts, this study systematically reviews and synthesizes fragmented evidence to strengthen the conceptual foundations of employee AIA and develop a coherent, process-oriented understanding of the construct. A systematic literature review was conducted using a five-step identification and screening protocol, resulting in 147 peer-reviewed studies. These studies were analyzed using the Theory–Context–Characteristics–Methodology (TCCM) framework to examine theoretical foundations, contextual patterns, construct characteristics, and methodological trends. The findings clarify the conceptual boundaries of employee AIA, distinguish it from related constructs, and reconceptualize AIA as a dynamic process through which employees interpret and adapt to AI-related organizational change. Specifically, employees interpret AI-related cues through interconnected cognitive, affective, motivational, behavioural, and relational mechanisms, resulting in divergent adaptation trajectories contingent on the availability of individual (e.g., self-efficacy and AI-related capabilities) and organizational resources (e.g., leadership support, training, and psychological safety). Building on this synthesis, the review develops a process-oriented conceptual framework that explains how employee responses to AI emerge and evolve across organizational contexts, while a structured TCCM-based research agenda identifies priorities for future theoretical and empirical advancement. The review advances employee AIA scholarship by providing conceptual clarification and a process-oriented reinterpretation of fragmented evidence, offering a stronger foundation for future research and evidence-based managerial interventions that support psychologically sustainable AI adoption.
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