In this blog post, we’ll break down how artificial intelligence is being applied across various areas of the fashion industry—including distribution, customer experience, and materials—into four categories, and examine potential challenges and solutions.
Do you remember the “Pokémon GO” craze from a while back? “Pokémon GO” was not just a game but a smartphone location-based service that applied augmented reality technology to gaming. It gained immense popularity among people of all ages and genders, driving up demand in related IT sectors such as mobile batteries, wireless internet, and used smartphones. Additionally, the Japanese business media outlet ‘Nikkei Trendy’ named ‘No-Look AI Appliances’ as the top predicted hit product for 2017. This concept refers to AI-equipped home appliances that operate automatically without the consumer having to press a button.
Artificial intelligence (AI) is currently a hot field, and the importance of related industries is growing. The fashion industry has also been integrating technology for quite some time, and the emergence of AI has had a significant ripple effect on the sector. In this article, we will examine how AI technology is being applied to the fashion industry by dividing it into four categories—big data, interactive robots (chatbots), voice interfaces, and materials—and discuss the anticipated challenges and solutions when implementing these technologies.
First, the combination of big data and AI has enabled personalized services for a large number of consumers. AI-based retail systems continuously learn consumers’ shopping habits and preferences, allowing them to more accurately identify which products and services customers are interested in. Based on this, companies can provide personalized recommendations, and customers can enjoy experiences tailored specifically to them. Additionally, big data helps predict upcoming trends and individual consumer demand, contributing to supply optimization and reduced inventory management costs.
The advent of the bot era has also brought changes to how the apparel industry operates. Chatbots are AI-powered interactive messaging tools, and retailers such as Burberry, Sephora, and Tommy Hilfiger have already adopted them to automate communication with customers. In the fashion industry, conversational commerce is crucial, and communication with customers is key to sales. In the past, humans were at the center of this process, but chatbots can converse with customers and provide recommendations and responses anytime, anywhere. Meanwhile, Rebecca Minkoff has introduced a self-checkout store where customers can make purchases and wear their items immediately without assistance from staff.
Voice interfaces allow users to control software using their voices. As many people associate with ‘Siri,’ voice interfaces enable customers to shop quickly using only their voice, from product search to purchase. Some retailers are conducting experiments combining voice and gesture interfaces, such as offering virtual experiences of overseas department stores through virtual reality (VR) shopping spaces or testing new payment methods that allow transactions with a simple nod of the head.
Finally, AI is driving change in the field of clothing materials. Recently, clothing made from fabrics embedded with computer systems has emerged, capable of responding to changes in ambient temperature and storing and regulating the wearer’s body heat. Additionally, there is a growing number of cases where clothing itself becomes an interface, such as the jacket created through a collaboration between ‘Levi’s’ and ‘Google,’ which allows users to control their smartphones by touching the sleeve.
However, due to the unique nature of the fashion industry, there are several challenges to commercialization. Because fashion products have very short lifecycles and trends change rapidly, the approach of investing in long-term research to launch new products—common in other industries—does not always work. By the time the results of a decade of research reach the market, the item may already have lost consumer interest. Therefore, the fashion industry needs a strategy to rapidly adopt and commercialize technology through close collaboration with the tech sector.
Another major obstacle is consumer mindset. Some customers believe that no further innovation is needed in shopping or prefer traditional purchasing methods. Even early online luxury platforms like ‘Net-a-Porter’ required significant effort to break the stereotype that luxury goods must be purchased in person at department stores. To change the perception that clothes must be tried on in person and bought from a salesperson, new purchasing methods must be naturally embraced through experience-centric customer experiences.
Regarding the adoption of artificial intelligence, the phenomenon of “digital overload” has also been raised as an issue. With the proliferation of online shopping, customers are experiencing “choice fatigue” as they are bombarded with an overwhelming amount of information through their mobile devices. While experts point out that AI could actually exacerbate this overload, conversational AI, on the other hand, has the potential to alleviate it. Conversational interactions provide customers with immediate and immersive experiences, helping consumers make rational decisions among countless alternatives. Furthermore, by accumulating specific data on unstructured and complex customer behavior, it is possible to design more efficient shopping experiences.
Clearly, there is significant demand and investment value for AI in the fashion sector. Given the rapid pace of digital device evolution, the industry needs to focus on long-term investment through active partnerships with technology rather than chasing short-term profits. First, we must accurately understand and analyze AI investments; we should not view AI merely as a tool for routine tasks but consider how to apply it to improve customer experience and develop interactive interfaces. For example, the issue of size discrepancies—a frequent source of customer complaints—can be addressed through big data. It is essential to consistently tackle these seemingly minor yet critical issues, and it is through this process that the true potential of AI will be realized.
