The textile industry's digital transformation is moving away from grand narratives and entering a new phase of 'small incisions, quick implementation.' The 2026 Textile Industry Digitalization Conference, held on May 7 in Keqiao, released a set of critical signals: AI fabric inspection has moved from concept validation to production line pilots; a digital dyeing process achieving nearly 99% water savings drew widespread attention; and small and medium-sized enterprises (SMEs) were explicitly advised to 'start with the most painful scenarios.'
From 'Big Systems' to 'Small Incisions': A Pragmatic Shift in Digitalization Paths
The clearest signal from the conference was that textile digitalization is no longer pursuing 'big and complete' solutions in one step, but instead emphasizes a five-step method: 'diagnose the current situation, select scenarios, supplement data, conduct pilots, and expand capabilities.' The three major directions proposed by Yan Yan, Vice President of the China National Textile and Apparel Council—deep AI implementation, full-chain efficient collaboration, and green manufacturing integration—all point to the same judgment: digitalization must be tied to specific business scenarios.
As the 'International Textile Capital,' Keqiao has been operating its '1+4+N' comprehensive intelligent agent system for several years. However, the conference's focus was not on the platform itself, but on three vertical tracks: printing and dyeing intelligent manufacturing, AI fabric inspection, and trade digitalization. This implies that the digital infrastructure led by government and platform-driven initiatives in recent years is giving way to enterprise-driven, scenario-validated value creation.
AI Fabric Inspection: The Game Between Technological Maturity and Implementation Cost
AI fabric inspection was the most discussed topic at the conference. Multiple service providers, including Shanghai Kaiqian Intelligent Technology and Nantong Julian Digital Technology, showcased solutions covering online defect warning, warp and weft density monitoring, and production anomaly recognition. Luo Yucheng, Deputy General Manager of Shaoxing Keqiao Weaving and Dyeing Industry Brain Operation Co., Ltd., bluntly stated that the industry still faces three major bottlenecks: difficulty in algorithm adaptation for complex fabrics, system instability in production environments, and high one-time investment for SMEs.
The pain points of traditional manual inspection—recruitment difficulties, fatigue-induced missed detections, and delayed problem identification—are clear enough. However, for AI inspection to truly replace manual labor, the 'last mile' problem must be solved. The conference suggested building a unified industry defect standard database, which is precisely the most lacking infrastructure at present. Without standard data, the generalization ability of AI models cannot be achieved.
Low-Carbon Dyeing: An Underestimated Digital Breakthrough
Compared to AI fabric inspection, the TDSD® low-carbon digital dyeing process released by Hangzhou Huanyu Digital Smart Technology is more disruptive. The technology, through self-developed inkjet equipment, new ink materials, and an AI color management system, achieves 'print-and-dye' production, saving nearly 99% of water, reducing carbon emissions by 33%, and cutting chemical usage by 21%. Under the increasing pressure of environmental compliance year by year, such data means that dyeing enterprises can significantly reduce wastewater treatment costs and carbon tax risks.
More critically, this solution essentially transforms dyeing from 'batch processing' to 'digital production.' Color formulas and process parameters are fully digitized, solving the problem of low efficiency in traditional sample-making while providing a technical foundation for flexible, quick-response supply chains. For small and medium-sized dyeing plants, this 'equipment + materials + system' package is easier to adopt than building their own MES or ERP systems.
Trade Digitalization: Low-Code Platforms Lower the Barrier
The digital management platform for trading companies shared by Shaoxing Getakesi Light Textile Technology adopts a low-code architecture, supporting a gradual, step-by-step construction path. This is particularly practical for the vast number of small and medium-sized traders with annual revenues under 50 million yuan. They can neither afford the high cost of customized ERP systems nor tolerate the functional redundancy of general-purpose SaaS. The low-code platform allows enterprises to start with one module, such as order management or inventory tracking, and gradually expand to a full-process closed loop.