China’s AI-driven manufacturing revolution accelerates in textiles and high-performance materials

BEIJING , China’s push to fuse artificial intelligence and digital technologies with longstanding manufacturing strengths is reshaping traditional industries from garments to materials, driving gains in productivity, product quality and green manufacturing while opening new markets for higher-value outputs.

According to the report by Xinhua, Bosideng’s smart factory in Changshu, Jiangsu Province, now moves a single jacket from raw fabric to finished product in three to four minutes during peak season. The company, which Xinhua says had amassed 1,520 patents by the end of September and sells down jackets in 72 countries with total global sales exceeding 200 million pieces, has over the past two years reworked its design and production model around AI and big data. “Bosideng has used the AI to overhaul its legacy design process and build a research and development model driven by AI and big data since 2024,” the report quoted Wang Chenhua, vice president of Bosideng.

Industry reporting by People’s Daily provides further detail on the factory’s automation scale, noting an AI system coordinating nearly 2,000 interconnected devices and achieving a 90% automation rate in key processes, which helped cut a traditional 28‑day production cycle to three days. The newspaper also reported Bosideng’s investment of over 1 billion yuan in digitalisation and smart manufacturing and a fall in inventory turnover from 175 to 118 days. According to China Daily and People’s Daily coverage, firms across the sector are adopting cloud factories, AI mannequins and virtual hosts to support agile, small‑batch production and reduce operating costs.

These developments in apparel are set against a broader policy backdrop. Xinhua highlighted the 2025 government work report’s commitment to combine digital technologies with manufacturing strengths and to support large‑scale AI models, new intelligent terminals and smart manufacturing equipment. In August, central guidelines on the “AI Plus” initiative were released to accelerate intelligent transformation across sectors, the Xinhua piece noted.

The shift is not limited to textiles. Xinhua and later accounts in China Daily and the Global Times reported rapid progress in high‑performance materials in Shanxi Province, where Huayang Group has moved from traditional coal activities into advanced carbon‑fibre production. “We have built a digitalized, visualized, and smart quality‑traceability system that helps us win the trust of high‑end markets in aerospace and new‑energy sectors,” Ge Peng, deputy general manager at Huayang, told Xinhua. China Daily and the Global Times describe a T1000‑grade carbon fibre line in Datong producing single filaments 6–7 microns in diameter with tensile strength above 6,400 MPa; the Global Times said a one‑metre bundle can lift roughly 200 kilograms. China Daily reported the Datong demonstration line began construction in June 2024 and that the project is a joint venture involving Huayang New Material Technology Group, the Datong city government and the Institute of Coal Chemistry under the Chinese Academy of Sciences.

Local industrial clusters are also using digital tools to move up the value chain. Xinhua described Changshu as a pivotal textile hub with more than 5,000 textile firms and annual output exceeding 500 million garments; the city has issued a white paper promoting AI‑driven development. In Henan Province, Xinhua reported, Luoyang’s Pangcun Township , a major steel‑furniture base , is deploying AI and IoT for smarter inventory and retrieval systems. “Our AI and IoT‑powered smart archive solution essentially gives the repository a ‘brain,’ enabling intelligent retrieval and automatic warning,” Zhou Xuguang, a local furniture company general manager, told Xinhua.

Taken together, these accounts suggest three practical outcomes for industrial decarbonisation and competitiveness. First, automation and AI cut cycle times and inventory, which can reduce embodied energy and emissions per unit through higher throughput and lower waste; People’s Daily’s figures on Bosideng’s cycle and inventory improvements exemplify that. Second, digital quality‑traceability systems, as described by Huayang, help producers meet exacting aerospace and new‑energy standards that favour domestically produced high‑performance materials over imports. Third, the adoption of cloud and AI tools enables smaller manufacturers to move from mass, low‑value production to agile, differentiated output that commands higher margins and supports investment in cleaner processes.

There remain practical challenges. Scaling intelligent systems requires sustained capital and skills, and the benefits vary by firm size and sector. Xinhua and People’s Daily note substantial corporate investment and university partnerships , Bosideng’s laboratory with Zhejiang University is cited as reducing prototype development from 100 days to 27 and cutting sample costs by over 60% , but broader diffusion will require policy support, workforce retraining and standards for data interoperability and energy efficiency.

As China presses forward with the AI Plus agenda, the onus for industrial decarbonisation will increasingly hinge on how firms deploy intelligence not only to raise productivity but to lower emissions intensity across value chains. The recent advances in smart garment production and high‑performance carbon fibre production point to the potential: intelligent factories that run faster, leaner and with finer traceability could become a core engine for both competitiveness and lower carbon intensity in traditional industrial heartlands.