Keywords
job performance
textile industry
smart manufacturing
workforce adaptation
How to Cite
Abstract
The textile industry is experiencing a profound transformation driven by the increasing integration of Artificial Intelligence (AI) across production systems. This narrative review synthesizes findings from contemporary empirical research to examine how AI influences operational processes and workers’ performance within the textile sector. The selected studies reveal broad consensus that AI strengthens production quality by enabling more precise detection of fabric irregularities and reducing dependence on manual inspection. Improvements in workflow coordination are also highlighted, as automated cutting systems, predictive scheduling tools, and intelligent inventory platforms support smoother and more agile production cycles. These technological developments collectively contribute to more sustainable and efficient manufacturing environments. At the labor level, the literature describes substantial changes in workers’ roles and expectations. Employees are increasingly shifting from repetitive manual tasks to responsibilities centered on supervision, technical maintenance, and interaction with digital interfaces. This transition underscores the growing demand for continuous training, particularly in areas such as troubleshooting, data interpretation, and foundational understanding of algorithmic processes. Alongside these opportunities for professional development, studies report notable apprehension among workers regarding employment stability, especially in contexts where companies have not implemented clear transition strategies or inclusive training pathways. Overall, the evidence indicates that AI represents both an opportunity and a challenge for the textile industry. Its successful adoption requires coordinated efforts involving industry leaders, policymakers, and educational institutions to promote equitable skill development, strengthen organizational communication, and support a socially sustainable transition toward AI-enabled textile manufacturing.
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Copyright (c) 2025 Erik Ortega-Lamar, Pablo Corrales-Negrete (Author)