From glamorous fashion weeks to high-end runway shows, the fashion industry constantly dazzles the world. However, this glittering industry also brings significant environmental challenges, such as overproduction, waste, and pollution. In response to these issues, the rise of artificial intelligence (AI) is poised to bring about a major transformation in both the textile and fashion industries. AI not only enhances the efficiency of design but also reshapes the entire supply chain, addressing challenges that were previously insurmountable.
Joshua Young, a brand consultant who has guided Nike and The North Face through digital transformations, along with Wayne Fan, co-founder and CEO of Frontier.cool, are at the forefront of understanding how AI will revolutionize the fashion and textile sectors.
Compared to other industries, the textile sector has been slow to embrace digitization. Four years ago, when 3D rendering technologies were just beginning to mature, Frontier.cool introduced AI-powered fabric digitization to the market.
Despite this, brands, both in Taiwan and the U.S., were initially hesitant. According to Wayne Fan, it wasn’t until 2023, when generative AI capabilities saw significant breakthroughs, that brands began to shift their attitudes, driven by rising labor costs in the U.S. Young estimates that around 75% to 80% of major fashion brands, each with annual revenues exceeding $1 billion, have now incorporated AI in various applications.
With over two decades of experience at industry giants like Nike and VF Corporation, Joshua Young now leads circular fashion initiatives at MOONFLARE, advocating for sustainable fashion practices. Previously, he spearheaded digital product creation and marketing transformations at VF Corporation, significantly reducing time-to-market and cutting costs for brands like Vans and The North Face. His innovative approach continues to drive digital innovation across global retail.
For brands such as Nike, GAP, and Calvin Klein, the process from launching a new season's collection to hitting the shelves used to take up to two years. During that period, accurately predicting consumer behavior was nearly impossible, leading to frequent overproduction. As a result, unsold inventory often required heavy discounting, or worse, was destroyed or sent to landfills—further exacerbating environmental issues. "The only solution is complete digitization," Young asserts.
By leveraging AI and data analysis, brands can make more informed decisions about which products to produce for the upcoming season. Designers can utilize generative AI to generate hundreds of design concepts quickly, while manufacturers can use AI-powered fabric digitization platforms to streamline the entire process. This approach transforms the traditional design-manufacture-sell process into a more efficient design-sell-manufacture model, ensuring that products are only made once there is consumer demand, thereby avoiding overproduction.
AI is not only tackling overproduction but also optimizing supply chain operations for greater sustainability. Through AI, brands can make better decisions about where to source raw materials and streamline the logistics of shipping finished or semi-finished products. This reduces time and carbon emissions throughout the supply chain.
Young explains that brands must consider numerous factors when selecting raw material suppliers, including price fluctuations, environmental regulations, and the impact of crop production (such as cotton) on local communities. Additionally, the location of textile and garment factories and associated tariffs must be factored in, along with transportation costs to distribution centers. AI helps brands conduct in-depth supplier analysis to continually improve operational efficiency and bring products to market more economically.
Wayne Fan notes that from 2025 to 2030, brands will face increasing ESG regulations, including carbon border taxes. Suppliers will need to comply, and to assist, Frontier.cool plans to launch an automated carbon footprint calculation system for the textile industry by the end of the year. This platform will help supply chain partners collect, process, and verify data to track greenhouse gas emissions throughout a fabric's lifecycle, ensuring compliance with ISO 14064 and ISO 14067 standards.
The introduction of AI will have a profound and lasting impact on the fashion industry, not only increasing production efficiency but also offering solutions to reduce environmental harm. However, Young cautions that many materials used in fashion, such as polyester and nylon, are synthetic and not biodegradable. These materials can persist in the environment for extended periods, potentially releasing microplastics. The industry should move away from using such materials.
Finally, Young highlights another significant application of AI in fashion: virtual try-on technology. Consumers can upload photos to see how a garment would look on them, offering a more realistic shopping experience and reducing return rates and waste.
In conclusion, AI is transforming how the textile and fashion industries operate, providing innovative solutions to the problem of overproduction. With AI, brands can make more precise production decisions, streamline design processes, and build more sustainable supply chains. As technology continues to advance, AI will play an increasingly critical role in driving the fashion industry toward a smarter, greener future.