Fashion is a dynamic business. Most apparel brands release at least two to four collections a year. While selling their current seasonal collections, brands identify market trends and materials and plan their next collections at least a year in advance. The sales period is around three months, and unsold inventory represents a financial loss.
Fast fashion companies are introducing new lines more frequently, shortening the time required to design, produce, and market new items.
Technology and Fashion
The fashion industry is no stranger to experimenting with cutting-edge technology: some of the most significant innovations include laser cutting, computer-aided design, and more recently, in the early 2010s, the use of 3D printing.
The fashion industry has experimented with basic AI and other cutting-edge technologies, such as the “Gucci Garden,” a collaboration with virtual world platform Roblox that the brand created in May 2021 to celebrate its 100th anniversary.
Non-fungible tokens (NFTs) are another area of innovation, as seen in Dolce & Gabbana’s Genesi collection, in collaboration with digital luxury marketplace UNXD, which sold for $6 million and set a sales record for an NFT.
Fashion companies are also using blockchain for product authentication, traceability and digital identity, including product authentication and traceability integrated by LVMH/Louis Vuitton.
Additionally, businesses are incorporating augmented reality into their marketing and retail strategies to create immersive and interactive customer experiences.
Game-changing technology
In 2021, fashion companies invested 1.6-1.8% of their revenues in technology. By 2030, that figure is expected to increase to 3-3.5%.
Generative AI has the potential to revolutionize the fashion industry, potentially increasing operating profits by $150-250 billion within three to five years. While the fashion industry is just beginning to adopt AI, the opportunities and challenges it brings are evident across all business processes.
Generative AI helps fashion companies improve processes, get products to market faster, sell more efficiently, and improve customer experiences. Generative AI can also support product development by analyzing large social media and runway show datasets to identify emerging fashion trends.
The Estée Lauder Companies and Microsoft have teamed up to launch an internal AI innovation lab to identify and address trends, inform product development and improve customer experiences.
Designers can use AI to visualize different materials and patterns based on past consumer preferences. For example, Tommy Hilfiger Corporation is working with IBM and New York’s Fashion Institute of Technology on the Reimagine Retail project, which uses AI to analyze consumer data and design new fashion collections.
Designers can also convert sketches and mood boards into 3D designs and 3D print them to speed up prototyping. Dutch fashion designer Iris van Herpen used AI to conceive and execute the visuals for her Autumn/Winter 2023 collection.
NOWNESS showcases Dutch designer Iris van Herpen’s imaginative use of AI.
AI and Sustainability
AI can help practice more sustainable fashion by optimizing resource use, recycling materials, and reducing waste through more precise manufacturing processes and efficient supply chain and inventory management. For example, H&M uses AI to improve its recycling processes, sorting and categorizing clothes for recycling, promoting a circular fashion economy.
AI can improve operational and supply chain processes by optimizing inventory management, forecasting sales based on historical data, and reducing overstocks and out-of-stocks. Brands such as Zara and H&M are already using AI to manage their supply chains and promote sustainability by optimizing stock levels and reducing waste. Zara has deployed AI and robots in its retail stores to speed up the pickup of online orders.
AI-powered virtual try-on solutions allow customers to see if clothes look good on them without having to physically try them on, improving the online shopping experience and reducing return rates. Virtual try-on is already a reality for digital companies such as prescription eyewear retailer Warby Parker and Amazon.
Another example is Modiface, which was acquired by French multinational personal care company L’Oreal in 2018, which offers AR-based virtual try-on of cosmetics and fashion accessories.
Virtual try-on helps buyers make better decisions and reduces returns. (Shutterstock)
Effective campaigns
AI can also deliver customized customer experiences: Some brands, like Reebok and Versace, are inviting customers to use AI tools to design products inspired by the brand’s feel and look.
AI-powered tools can help marketing teams target and maximize the effectiveness of their communications campaigns, potentially reducing marketing costs.
The fashion industry includes everything from small businesses to global chains, haute couture to ready-to-wear, mass market to fast fashion, and each brand needs to understand where AI can create value for their business without diluting their brand identity.
But the biggest challenge is to avoid homogenization: generative AI does not replace human creativity, but rather creates new spaces and processes.
Creativity and innovation are the soul and heart of any fashion brand, and AI should be a tool that enhances and supports this. Fashion designer Hussein Chalayan has said, “Fashion will be reborn through technology, new fibers, and new ways of making clothes.”
The pitfalls of AI
Fashion companies need to be prepared to manage the risks that come with new technologies, especially with regards to intellectual property, creative rights and brand reputation. One of the main issues is the potential infringement of intellectual property related to training data.
GenAI models are trained on vast design datasets that often contain copyrighted works, which can lead to legal disputes over originality and ownership. Related risks include bias and fairness in generative AI systems, which could call into question the reputations of brands that rely on the technology.
Another concern is the ambiguity surrounding creative rights in the age of AI. It can be difficult to determine who holds the creative rights of a design: the designer who conceptualized the idea, the developer who created the AI, or the AI itself. This ambiguity can dilute the authenticity of a brand’s creative expression and damage a brand’s reputation if consumers perceive the brand as less innovative or trustworthy.
