The Double-Edged Impact of Artificial Intelligence on Employee Performance A Systematic Literature Review

Abstract

Artificial Intelligence (AI) has rapidly transformed workplaces by reshaping employee roles, organizational processes, and performance outcomes. While AI enhances productivity, decision-making, and innovation, it simultaneously introduces challenges such as job insecurity, skill obsolescence, algorithmic bias, surveillance concerns, and employee stress. Existing studies present fragmented evidence regarding AI's positive and negative effects on employee performance. Therefore, this study systematically reviews the literature to synthesize current knowledge on the dual impact of AI in organizational settings. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, peer-reviewed studies published between 2018 and 2026 were reviewed from Scopus-indexed journals. The findings reveal that AI positively influences employee performance through automation, improved decision support, personalized learning, and enhanced collaboration. Conversely, excessive AI dependence may reduce employee autonomy, increase technostress, create ethical concerns, and negatively affect psychological well-being. The review develops an integrated conceptual framework illustrating both the enabling and inhibiting mechanisms through which AI influences employee performance. The study also identifies research gaps and proposes future research directions focusing on responsible AI adoption, employee resilience, organizational culture, and human-AI collaboration.