Artificial Intelligence in Manufacturing A Perspective on Productivity Gains and Labor Displacement
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Abstract
The integration of Artificial Intelligence (AI) into manufacturing has become a key driver of industrial transformation in the era of Industry 4.0, offering substantial gains in efficiency, productivity, and operational performance. However, its implications for human labor remain a critical concern. This study aims to examine the dual impact of AI adoption in manufacturing, focusing on both technological benefits and socio-economic consequences, particularly labor displacement, job transformation, and workforce sustainability. This research employs a systematic literature review of interdisciplinary studies published between 2010 and 2024, using thematic synthesis to analyze three key dimensions: labor displacement as a structural risk, the limitations of job transformation, and the emergence of human-centered AI. The findings reveal that AI disproportionately affects routine and mid-skilled jobs, contributing to labor market polarization and increasing risks of structural unemployment. While new high-skill roles emerge, their limited accessibility constrains workforce transition. The study highlights the need for a human-centered approach that integrates technological advancement with reskilling initiatives, labor protections, and inclusive policies. It contributes by providing a structured synthesis that bridges efficiency-driven and labor-oriented perspectives in AI-driven manufacturing.
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This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Accepted 2026-04-12
Published 2026-04-14
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References
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