Accelerating Digitalization in Wool Textile: AI Restructuring Global Supply Chains from Dalang

One out of every five sweaters in the world comes from Dalang, Dongguan, a wool-knitting town with an annual transaction volume exceeding 72 billion yuan. It now serves as a window into the digital transformation of the wool industry. The 95th International Wool Textile Conference, themed 'Smart Weaving the Future: Wool's Health and Digital Life,' signals a fundamental shift: traditional wool textiles are no longer just scale-driven processing chains but complex ecosystems reshaped by AI, data, and consumer experiences.

Structural Divergence in Industry Data

Data from the China National Textile and Apparel Council reveals a nuanced picture. From January to April, revenue of large-scale enterprises edged down 0.3% year-on-year, but total profit surged 19.3%, pushing the profit margin to 2.9%. This indicates that companies are relying on efficiency gains rather than scale expansion. Meanwhile, retail sales of apparel, footwear, hats, and knitwear by units above the designated size reached 512.13 billion yuan, up 8.1% year-on-year, showing resilient domestic demand.

However, investment data exposes internal divergence: textile fixed-asset investment grew 10.8%, while apparel and chemical fiber investments fell 10.3% and 14.5%, respectively. Capital is flowing toward more automated and intelligent segments, while labor-intensive garment processing and basic chemical fiber production face overcapacity and margin compression. From January to May, textile and apparel exports totaled 116.73 billion USD, up 0.1%, with textile exports rising 1.7% and apparel exports falling 1.6%, confirming that intermediate goods have stronger export resilience than finished products.

AI Penetration: From Efficiency Tool to Business Paradigm

AI applications in wool and broader textiles have moved beyond the proof-of-concept stage. The case of Jiangsu Yueda Textile is exemplary: through smart manufacturing, labor per 10,000 spindles dropped by about 70%, labor productivity quadrupled, energy consumption fell 15%, and processing costs decreased 26%. This suggests that the payback period for smart transformation is shortening amid rising labor costs and recruitment difficulties.

Design efficiency gains are equally striking. Semir's AI-assisted design system boosted overall R&D efficiency by 35% and pattern design efficiency by over 200%; Bosideng's 'AI Aesthetic Brain' reduced sample development costs by over 60%. For wool textiles, where pattern, texture, and color design are complex, AI can drastically shorten the cycle from trend capture to prototyping.

Deeper changes are occurring at the organizational level. Anuoqi's case shows an ecosystem integration from 'dyestuff to ink to digital printing to AI design and IP cultural creation,' meaning companies are no longer just manufacturing nodes but data- and algorithm-driven platform organizations. IWTO data shows the global AI market reached 757.58 billion USD in 2025, projected to exceed 900 billion USD by 2026, redefining the comparative advantages of traditional industries like textiles.

Experience Economy Driving Supply Chain Restructuring

Consumer stratification is reshaping the value logic of wool products. Health, emotional connection, and self-expression are core demands, with social media accelerating information dissemination and purchase decisions. This imposes two direct requirements on wool supply chains: flexible production for small batches and diverse varieties, and traceability with green certification from fiber to garment.

Dalang's cluster advantage—producing over 900 million garments annually—must combine with digital capabilities to meet these changes. Green technologies like non-aqueous dyeing and digital printing are accelerating adoption, improving resource efficiency. Industry data shows 63.2% of key links are digitized, above the national manufacturing average, with 30 textile enterprises on the 5G factory list in 2024.

For buyers and foreign trade companies, the traditional model of 'taking large orders with long lead times' is fading. The new standard is data-driven rapid response and sustainable supply chain management.

Practical Recommendations

For Buyers - Prioritize suppliers with digitized key links (e.g., AI quality inspection, smart scheduling) for higher delivery stability and consistent quality. - Monitor investments in green dyeing and digital printing, as these directly affect access to environmentally stringent markets like the EU. - Leverage AI-assisted design tools to shorten sample development from 3-4 weeks to 1-2 weeks, enabling faster response to fast fashion and personalized orders.

For Foreign Trade Companies - Shift investment focus from capacity expansion to smart transformation, especially automation and digitization in spinning and weaving, to reduce unit labor costs. - Establish a full-chain carbon footprint traceability system, a hard requirement for entering international brand supply chains. - Monitor demand shifts in Southeast Asian markets, using China's export advantage in intermediate goods like chemical fibers and fabrics, while moving finished processing to lower-cost regions and retaining high-value design and R&D.