How AI/ML and Big Data are Diving Innovation in the Fashion Industry
How AI/ML and Big Data are Diving Innovation in the Fashion Industry

According to a recent McKinsey Global Fashion Index (MGFI) report, a record 69 percent of companies in the fashion world were value destroyers in 2020, up from 61 percent in 2019 and 28 percent in 2011. About 7 percent of businesses completely withdrew from the market because of financial difficulties or being acquired by peers. The global fashion industry is reclaiming its footing in the world and reinventing itself to meet the new demands of customers, while digitization serves as a growth hub. Despite this, the industry still faces formidable obstacles, including fluctuating customer demands, supply chain interruption, and time-to-market pressure, among other things. 

In 2021, technology accounted for about 1.6 to 1.8 percent of sales for the fashion industry, and this percentage is expected to rise to 3.0 to 3.5 percent by 2030. The anticipated increase is being driven by the notion that technology will provide a competitive edge in both operations and customer-facing activities, which companies have been focusing on more recently. Processes may be accelerated, sustainability could be improved, and customer experience could be enhanced using Artificial Intelligence (AI), Machine Learning (ML), and Big Data.

In the coming years, data will be the key to revealing the insights required to adjust to change and reengage customers. However, the pandemic has shown a significant deficiency in data collection and analysis throughout most of the businesses in the industry. The data gap has broadened, some data-savvy fashion and luxury brands have significantly improved their market worth, while others have lost ground to the competition. Indeed, more than 90 percent of the rise in the industry's worldwide market value during the pandemic can be attributed to the 25 top-performing retailers, the majority of whom are shining examples of the dramatic move to digital, data, and analytics. 

Current Innovations in Fashion Industry Powered by AI/ML 

AI as a Creative Collaborator - Through personalization, interactive retail spaces, augmented reality (AR), cutting-edge technology, more effective business practices, and access to consumer and industry data, fashion companies are adopting these new approaches to showcase their products to customers. A new paradigm has emerged in the fashion industry, where AI systems are seen as creative collaborators. AI can assist in the design of new apparel by fusing physical capabilities and technology to extend designers' imaginations. 

Customer Insights - By gathering more sophisticated data, fashion designers may use technology to better understand consumer expectations and enhance their designs. Pictures posted online can now be used to infer customers' preferences, likes, and styles. These photographs are analyzed using big data and AI algorithms, which can be useful tools for predicting upcoming trends. While AI can be used to eliminate manual labor, it can also be used to gather information on the social media interests of the general public. AI is revolutionizing how brands approach the design and development process by predicting what customers will want to wear next.

Eliminating Supply Chain Bottlenecks - The fashion industry's supply chain is very intricate involving a dispersed network of manufacturers, suppliers, retailers, and customers. The process requires enormous capital upfront, not only does the brand have to invest funds into making its product line, but it must also stock inventory before it knows how well those items will sell. The lack of visibility into this complex network creates a lot of inefficiencies and ultimately results in delayed deliveries to the market. According to Research and Markets, 2021, an AI-enabled supply chain's degree of efficiency will result in over 65% effectiveness in minimizing risks and overall costs. Retailers can predict top-selling items in advance by switching from conventional formulas to new manufacturing models.

Growth Driver - This has not only improved product flow but has also exposed manufacturers and brands on a far bigger scale than in the past. Due to the enormous number of stakeholders involved in global supply chains, end-to-end transparency is getting more and more difficult. Technology can help us address this issue. Al uses the original design production model, which allows for a more effective manufacturing procedure, to build stocks only when they are purchased. Fashion brands can now study and analyze data from all points of the supply chain before efficiently addressing disruptions. AI makes sure that everyone in the chain can access data, track status, plan deliveries, and carry out transactions in real-time while assisting in tracking the status of items as they move through the supply chain.

Sustainable Business Models - The problems of ethics, sustainability, a lack of workforce, and lengthy lead times that arise when firms outsource production to countries with lower labor prices can be reduced using technology. Retailers are moving some production back home in anticipation of the emergence of smart manufacturing in the hopes that their investments in technology and digital transformation projects would eventually balance out the drawbacks and propel a smarter future. Manufacturers can foresee and better prepare for their supply needs by using AI-powered solutions, which are dependent on factors like weather, traffic, tolls, and other factors. Additionally, in order to find other routes and expedite deliveries, clothing brands have automated their supply chain and logistical processes using machine intelligence.

How AI/ML is Shaping Future Trends in Fashion Space

Brands could have a sizable competitive edge if we combine inventory tracking with AI's strong data prediction skills for trend forecasting. Brands may instantaneously access data that enables timely planning of the appropriate designs and quantities rather than only depending on conventional methods of trend forecasting, which necessitate observation and data collection from fashion designers, trend spotters, and influencers.

Consider FINERY, for instance, the British clothing brand has developed an automated tool for organizing one's wardrobe that, using analytics, keeps track of the purchases made by its female consumers and displays them in a digital wardrobe. Women may create ensembles using their own clothing and even shop from more than 10,000 stores using the platform. Intelligence Node is another remarkable example, which enables users to follow trends in real-time. The customer has the option to insert specific keywords, navigational patterns, price points, and more. Users can follow the exact or closest matches to their product on the AI-driven search discovery platform, which can offer valuable insights regarding competitive differentiators.

Live video streaming has significantly impacted our daily lives. Instagram commerce has dominated the post-COVID market in 2022, dominating everything from virtual events to wellness programs. New streaming media formats with high-definition visuals, faster connectivity, and data transfer across the Internet of Things devices are possible thanks to 5G technology. Customers can now 'try on' designs before buying them. Some popular brands, such as Tommy Hilfiger and Gucci, offer digital showrooms to evaluate the market's interest.

Interestingly, selling digital apparel is also becoming increasingly common. For instance, Louis Vuitton created "skins" for League of Legends characters, and the latest partnership between Polo Ralph Lauren and Bitmoji, which allows customers to design their own Bitmoji appearance using the brand's new mix-and-match wardrobe, further exemplifies the allure of the e-wardrobe. 

Way Forward

One of the few constants in the fashion industry is that nothing remains the same. Personalization, store technology, and end-to-end value chain management are three potentially important areas in which the fashion industry could invest digitally over the next few years. Fashion decision-makers must think about how to leverage technology to foster creativity, streamline processes, and generate value from innovation that can endure in the near future.

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