AI in fashion is transforming the US$3 trillion industry all the way from how brands design their products to how those products are sold.
One of the biggest industries in the world, the global fashion industry is estimated to be worth around US$3 trillion, representing 2% of global GDP. Artificial intelligence (AI), one of the most important disruptive forces in this industry, is transforming the fashion industry at every level – all the way from designing, manufacturing, and logistics, to marketing and sales.
Where the two forces meet, a plethora of opportunities have arisen for enterprising people and companies to exploit.
AI in design and manufacturing
Before every season, designers create new lines of clothing or accessories. However, as the industry changes rapidly and dramatically, with new styles and patterns making entries every week, the design process can become cumbersome.
While traditionally, design and manufacturing quantity was based on the previous year’s sales, predictions could easily go wrong due to factors like changing customer buying patterns or changes in styles. This is where AI comes into the picture.
Using branches of AI like machine learning, natural language processing, deep learning, visual recognition, and data analytics, apparel companies have a new arsenal of tools at hand for trend forecasting and demand planning.
According to a study by McKinsey, AI can reduce forecasting errors by 20-50% and more accurately forecast trends, thereby minimizing overstocking and optimizing turnover. When designers can anticipate what kind of style will work or fail, they can drive relevant sales.
Additionally, AI can also help in the manufacturing, making labor-intensive processes faster and more efficient, and all the while ensuring quality.
For instance, there are now AI-enabled sewing robots that can automatically stitch any pattern, size, and shape of clothing. There are also robots that are designed to detect any defects and automatically make adjustments accordingly, which are believed to have higher accuracy than the human eye. Brands like Zara and H&M are now using robots for knitting sweaters.
AI in marketing and sales
Akin to any other industry, the fashion industry relies on marketing and driving sales. Ultimately, what’s the point in designing and manufacturing clothes, if there is no one to buy them?
Fashion brands are now increasingly using AI and ML to automate and enhance the sales process using predictive analytics and guided sales processes.
In retail stores, AI can monitor customers’ activities to identify what products they prefer to buy. For instance, clothing store Uniqlo uses AI-powered UMood kiosks to measure customers’ reactions to the color and style of products they are shown. Based on these reactions, the kiosk recommends products without the customer even having to push a button.
Retailers can also use AI-powered smart mirrors, which let you try on multiple outfits virtually without going through the hassle of actually wearing each item.
Such changes apply to sourcing the right fashion as well. Tech startups have built B2B solutions allowing customers to take pictures of other people wearing items they want and find similar items available on sale through smart image recognition systems. This is enabled by computer vision-based visual search technology. The algorithms can also recognize multiple objects within a single picture, thereby enabling the sale of a range of items.
Additionally, through AI-enabled shopping apps, customers can also take screenshots of apparel online and then shop for the same clothes, accessories, or styles. Through this, customers can either find the exact outfit or brand, or similar styles.
Some retail stores also have apps that allow customers to virtually try on clothes or even makeup from the comfort of their home.
For instance, Stitch Fix, an online personal styling service, uses ML algorithms based on design trends, style trends, customers’ personal experiences, and their feedback to help human stylists deliver personalized recommendations to the customers on a regular schedule. The customers do not even have to step out of the comfort of their homes, can keep the products they like, and return those that they don’t.
Furthermore, fashion brands are using conversational assistants like chatbots and voice assistant devices such as Amazon Alexa, Apple Siri, and Google Home, to gather deeper insights into customers’ purchase patterns by asking them questions related to their past or desired purchase or by analyzing their purchase history. The conversational assistants can then suggest related and add-on products in the future as they now know customers’ sizes, preferred styles, and favorite brands.
AI in logistics and shipping
As mentioned earlier, AI can be used to accurately predict inventory demand and reduce wastage. In fact, according to the McKinsey study, using AI-integrated supply chain tools can help reduce overall inventory levels by 20-50%.
It can also help companies automate logistics and supply chain processes, thereby resulting in faster deliveries and reduced shipping costs. For example, when there is traffic or bad weather, AI can help pick alternate delivery routes.
Stitch Fix, which integrates AI into nearly every stage of the fashion project journey, uses algorithms to optimize pick up and shipments. Additionally, it uses algorithms to optimize various inventory management issues such as restocking inventory after customers receive their items, figuring out how many of each style to purchase to meet demand, and not be left with extras that won’t sell.
AI in detecting counterfeit goods
According to an OECD report, trade in counterfeit and pirated goods accounts for 3.3% of global trade. Footwear and clothing constitute the bulk of the trade at 22% and 16% respectively.
As the trade of counterfeit goods has risen steadily over the years, computer vision can be a valuable tool for spotting counterfeit products. Brands can use AI technologies to verify the authenticity of potential counterfeit products and tackle issues of infringement and counterfeiting, reducing the likelihood of further losses.
Entrupy offers a machine learning app to help brands detect counterfeit items based upon a deep database of authentic luxury items. For instance, to examine the authenticity of a luxury bag, the company uses artificial intelligence to microscopically examine the exterior, interior, and physical components of the bag. It then compares these details to over 30 million images in its database to determine the bag’s authenticity. The company claims to have a 99.1% accuracy rate.
A sustainable way forward
The fashion industry accounts for 10% of humanity’s carbon emissions, 20% of the world’s industrial wastewater, and is the second-largest consumer of water worldwide. Even worse, every year, 85% of textiles end up in landfills – that’s the equivalent of one garbage truck full of clothes every second.
As alarming as these numbers are, AI can help to provide sustainable solutions. Overproduction is one of the major reasons for the industry’s adverse impact on the planet. AI’s aforementioned uses in accurately predicting inventory demand, forecasting trends, and understanding customer preferences can all help to reduce wastage.
Further, to promote a circular economy, AI can design circular products and materials and also help operate circular business models. It can further analyze the factors that contribute to a brand’s carbon footprint and identify sustainable supply partners and modes of transports.
Privacy concerns regarding AI
As businesses using AI generally collect a large amount of user data to identify preferences, analyze trends, improve consumers’ experiences, and track competitors’ activities, users’ privacy and the security of the collected data have become areas of concern.
Privacy has become complicated for a number of reasons, such as the low cost of storage resulting in information being stored for longer than intended, data being used for purposes different from those intended, and the chances of data for a certain individual containing data of others.
While AI is taking product customization to another level and offers a slew of benefits to the fashion industry, the key is for companies to take privacy and security seriously and initiate better measures to protect users’ data.
Whether these efforts are driven by self-regulation or legal stipulations, it will be important to balance two priorities: data protection shouldn’t be so little that customers don’t adopt AI-related applications, but at the same time, regulations shouldn’t be so stringent as to hamper innovation. It’s a balancing act left for regulators and apparel industry titans to grapple with, and consumers will surely feel the impact in years to come.