Textile industry faces AI barriers due to data and skills gaps

A white paper published by the International Textile Manufacturers Federation (ITMF) and the Institut für Textiltechnik of RWTH Aachen University (ITA) identifies data integration, skills shortages, and governance gaps as the primary obstacles to AI adoption in the textile and apparel industry. The report suggests that the sector is not under-digitalized but rather “digitally fragmented,” with decades of digitalization resulting in abundant but disconnected data systems.

While AI is already providing value in areas such as predictive maintenance, energy optimization, and fabric inspection, the authors warn that AI can amplify existing flaws in poor-quality data. The industry is facing structural pressures including demographic decline, market volatility, and increasing demands for sustainability and traceability.

In garment manufacturing, automation is increasingly being applied to surrounding processes such as material transport, warehousing, and cutting. While automated systems like CNC knives and laser cutters achieve high fabric utilization, sewing remains a largely human-led operation due to the complex, unpredictable nature of fabric behavior. In vertically integrated factories, sewing typically accounts for 30% to 50% of the workforce.