One out of every five sweaters globally comes from Dalang, Dongguan. Behind this figure lies an industrial cluster producing over 900 million garments annually, with a full industry chain transaction value exceeding 72 billion yuan. The 95th International Wool Conference, held here in late June, set its theme as 'Intelligent Weaving the Future: Wool's Health and Digital Life,' directly addressing the core challenge for the wool industry over the next decade: how can traditional manufacturing, when natural fibers meet digital technology, avoid being overwhelmed by the AI wave and instead reshape its value?
The Scale Effect of Industrial Clusters and Transformation Pressures
Dalang's rise is no accident. As a woolen town nurtured during China's reform and opening-up, it absorbed the transfer of the global wool industry chain, forming a closed loop from raw materials, design, and weaving to finished garments. This clustering reduces logistics and transaction costs and enables 'quick response'—factories in Dalang can complete small-batch reorders within days, exactly the flexible supply capability fast-fashion brands demand.
However, scale brings inertia. R&D spending intensity among China's textile enterprises has risen from 1% at the end of the 13th Five-Year Plan to 1.3% in 2024, but many small and medium-sized wool enterprises face funding shortages and talent gaps for intelligent upgrades. Of Dalang's 72 billion yuan transaction volume, traditional OEM still accounts for a significant share, with limited brand premium. This means the next growth driver lies not in expanding volume but in using digital tools to boost value per unit.
Intelligentization: From Replacing Labor to Restructuring Cost
China's textile sector has achieved a 63.2% digitalization rate in key processes, above the national manufacturing average. In the wool industry, this translates to AI-based defect detection, automated winding, and intelligent sorting. For instance, Jiangsu Yueda Textile's 'lighthouse factory' reduced labor per 10,000 spindles by 70% and processing costs by 26% through smart manufacturing.
A deeper shift is the reorganization of production factors. As AI agents begin 'working' en masse, with IDC predicting billions of digital workers by 2030, the cost structure of wool factories will be rewritten. Traditionally, labor accounts for 15%-25% of garment costs; after intelligentization, computing power and electricity become major expenses. The deep coupling of 'energy-computing-data-manufacturing' will alter site selection—proximity to data centers versus labor pools becomes a strategic choice.
Experience Economy: Wool's 'Health' Narrative and Brand Premium
The conference theme of 'Health and Digital Life' captures two consumer trends. First, global preference for natural fibers is rising, with wool's breathability, warmth, and biodegradability fitting environmental and health demands. Second, social media and AI recommendation algorithms reshape purchase decisions—a sweater's 'story' and 'scene' matter more than its material.
This means wool companies must shift from 'selling fabric' to 'selling experiences.' Brands like Anta and Erdos have embedded 'Chinese design' into global mid-to-high-end markets through cross-border acquisitions and multi-brand operations. A more radical example is Anoky, a traditional dye maker building a chain from 'dye to ink to digital printing to AI design to IP cultural products,' extending wool from manufacturing into cultural creativity. For Dalang's factories, future clients may not be brand owners but niche designers or 'one-person companies'—China's new self-employed businesses grew 47% year-on-year in the first half of 2025, demanding extreme supply chain flexibility.
Global Supply Chain: Certainty Amid Uncertainty
China's textile exports have exceeded $300 billion for six consecutive years, with intermediate goods like chemical fibers and fabrics providing stable support. However, data from January to May this year shows garment exports fell 1.6% year-on-year, while textile exports rose 1.7%, reflecting weak end-consumer demand but resilient intermediate trade.
The IMF has cut its 2026 global growth forecast to 3.1%, with geopolitical conflicts and shipping disruptions raising trade costs. In this context, Dalang's cluster advantage becomes a source of 'certainty'—a complete chain reduces the need for cross-regional sourcing, dampening external shocks. But over-reliance on a single market carries risks; companies must accelerate overseas capacity and localization. The 'going out' practices of Hengli, Weiqiao, and others show that global footprints hedge regional risks.