From Technological Substitution to Institutional Response: A Systematic Review of Anxiety, Resistance, and Governance Transformation among Low Skilled Workers in the Age of Artificial Intelligence

Abstract

Artificial intelligence and robotic technologies are fundamentally reshaping labour markets and pose multifaceted challenges to workers engaged in routine and low-skilled tasks. This study reviews the principal scholarly contributions from both domestic and international literature over the past decade. Extensive empirical evidence shows that AI and robotics can substitute for rule-based, codifiable routine tasks, leading to contractions in low-skilled occupations and downward pressure on wages, with displacement effects extending from manufacturing into cognitive roles such as clerical work and customer service. Yet displacement is not the whole story: when firms adopt AI as an augmentative tool rather than a replacement mechanism, it can raise worker productivity and contribute to job creation. In terms of wages and job quality, automation has intensified income inequality between high-skilled and low-skilled workers, while algorithmic management and monitoring have reduced employees’ autonomy and perceived work meaningfulness, contributing to “AI anxiety”, characterised by persistent concerns about job loss, skill obsolescence, and diminished control. Survey evidence further suggests that public attitudes towards AI combine optimism with apprehension, and that most respondents oppose granting AI systems final authority over hiring and dismissal decisions. In response, trade unions have increasingly pursued algorithmic transparency and stronger technology governance rights through collective bargaining, and governments are accelerating legislative initiatives to establish and protect workplace technology rights. This review highlights clear gaps in existing research, including limited evidence from developing-country contexts, insufficient attention to within-occupation heterogeneity, an incomplete account of the psychological mechanisms underlying AI anxiety, and a shortage of rigorous evaluations of reskilling policy effectiveness; future research should therefore strengthen cross-national comparisons, longitudinal tracking, and interdisciplinary collaboration to support the development of a technology governance framework that balances efficiency with equity.