AI Fashion: 7 Industry Applications
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Whether you’re scouting sales, scrolling through social media to check out trends or deciding on outfits for a vacation, fashion can be fun. It can also be vexing for both shopper and retailer (fit!), as well as environmentally hostile (most returned clothing ends up in a landfill).
Can artificial intelligence help the fashion and apparel industry solve these un-fun problems?
Artificial Intelligence in Fashion
AI helps nearly all parties in the fashion ecosystem solve the above problems, plus a few more. Applications help both customers and manufacturers sort out the fit situation, which will make shoppers happier and reduce the industry’s environmental impact. Designers use AI to create fabrics and garments; consulting firms use it to predict trends for their manufacturing clients.
The magic lies in data collection. Repairing the fit issue, trends forecasting and even authenticating upscale items (Cartier watches, Birkin bags) are all divined by collecting data. AI can collect, process, and draw insights from all sorts of data, from social-media images to bodily functions such as heart rates and perspiration.
“We are at the very early phases of this and it’s been mind-blowing already.”
“We are at the very early phases of this and it’s been mind-blowing already,” said Hussain Almossawi, a designer and CGI (computer-generated imagery) artist based in New York City. “If that tells us anything, it’s that there is way more to come.” Machine learninghe added, “is all about taking in data, learning from what’s out there, and giving us an output based on what we are looking for.”
7 Examples and Applications of AI in Fashion
With that grounding, let’s look at the ways AI can make fashion smarter and more sustainable.
AI Can Fix Fit
Ill fit is the top reason for returning clothes bought online, and returns can cost a retailer up to 38 percent of the item’s original price, said Carlanda McKinney, founder and CEO of Bodify, an Overland Park, Kansas-based startup dedicated to helping solve the fit issue.
Bodify asks shoppers for photos, then uses computer vision to determine their measurements. Machine learning maps the measurements against data the company has stored. The end result for shoppers is a list of brands that fit them in the size they think they are. “You’ll discover these brands you didn’t even know about,” McKinney said.
Bodyfit’s data will help manufacturers cut garments to sizes that actually fit people, coordinate sizes of different types of garments (for instance shirts and jeans) and determine the best place to have their garments made. “The same pair of jeans can be made in China and in Indonesia, and they’ll fit differently,” McKinney said.
Fit for Everybody, a startup based in Princeton, New Jersey, provides shoppers with a video that shows them exactly where to measure themselves. Designers, who are Fit for Everybody’s paying customers, use the data to make patterns more in line with customers’ measurements. “You’re basically making clusters, you’re making five sizes that are going to encompass as many people as possible,” said Laura Zwanziger, founder and CEO. “The goal is to optimize each cluster.”
Fit for Everybody’s data will also help manufacturers improve consistency in grading, the term given to sizing up and down from the fit model size. “I want this to be seen as a product that makes their day easier,” Zwanziger said.
AI Helps Make Decisions
Does this color look good on me? Retailers can help customers answer that question with AI-powered virtual styling tools that assist customers in choosing items for their body type, skin tone and apparel needs.
One example: Styleriser, a B2B German company that makes a software that employs AI in image consulting. Customers upload a picture to the retailer’s online store and a virtual stylist analyzes the photo. It recommends the best colors for the person’s skin tones and gets specific (wear cream instead of white, or charcoal gray instead of black). The tool boosts confidence in shopping, which in turn increases purchasing readiness by 80 percent, said CEO and cofounder Mark Hunsmann. This also means fewer returns, which contributes to the industry’s sustainability, he added.
AI Helps With Design
Almossawi taps AI for inspiration and idea generation; it’s helped him generate more ideas than he could without it. “As part of every designer’s process, the early phase involves a lot of explorations and ideation sessions” ranging from bouncing around blue-sky ideas to brainstorming with colleagues. AI, he said, aids collaboration by expanding person-to-person collaboration to human-to-machine collaboration. “As crazy and interesting as AI is, it’s probably just in its infancy, and I can only see it getting better and doing much more than outputting images,” he said.
One example: Almossawi used AI to create a line of garments based on the Japanese kimono. “I thought it would be cool to look at designing different silhouettes with different kinds of textures and details,” he said.
AI Aids Merchandising
Use of AI-driven tools augmented and virtual reality (AR and VR) help online shoppers more fully comprehend what a garment looks like, and how it will look on them. Certain apps enable customers to project garments onto their actual bodies, then play with color, texture and accessories to get a look that’s just right, according to Tech Fashionista.
“Product placement is a huge part of building hype around a product…With AI, you can quickly generate cool and relevant backgrounds for your product in different styles.”
AI can also put products in the right environment, Almossawi said. “Product placement is a huge part of building hype around a product and telling a story of what the product is, and what it was designed for,” he said. “With AI, you can quickly generate cool and relevant backgrounds for your product in different styles.”
AI Can “Green” Fashion
In the fashion trade, green is the new blackas apparel manufacturing accounts for as high as 8 percent of the world’s greenhouse gas emissions and 9 percent of annual microplastics in the oceans, according to the UN Alliance for Sustainable Fashion. Nearly all of returned items end up in a landfillas restocking returns is often not financially feasible for retailers and high-fashion brands don’t want to devalue their names by selling to deep discounters.
AI can help on several fronts, starting with trends forecasting. Deciding what customers want, then mass producing that item, is a game of chance: Bet wrong, and a manufacturer will end up with a lot of unsold clothing. Several firms use AI and machine learning to analyze images on social media, taking note of prints, shapes and color to help their manufacturer clients figure out what’s going to sail and what’s going to sink. These companies also use AI to help brands figure out pricing strategies and steer clear of trends that are on their way out.
AI Can Reduce Counterfeiting
Who wants a fake Birkin bag? Nobody, especially someone who’s paid a minimum of $40,000 for the real thing. Two applications of AI can help prevent embarrassing moments such as these.
One, a tool created by accounting giant Deloitteuses AI to spot design infringements. The tool, nicknamed Dupe Killer, uses information from millions of photographs to detect subtle but distinct design elements, for instance the shape of an item, a color or even stitching pattern unique to the object. Dupe Killer helps brands spot and go after companies that are unlawfully using their design trademarks, explains this article in Vogue Business.
Another solution uses computer vision, a field of AI, to authenticate “real” items and thus help customs officials and others along the supply chain spot fakes, according to The Tech Fashionista.
AI Can Advance Wearables
AI-powered wearable devices, such as fitness bands that track heart rates, motion and performance are already on the market. It’s a big one, projected to reach $42.4 billion in sales by 2023, according to digital transformation company eInfochips.
Hussain Almossawi, the designer, predicts this use extending to apparel. Implemented into garments, AI could result in smarter fabrics, clothes better for sports and performance, and clothes more reactive to the body, he said. “For example, materials out there can sense when the body is hot or sweating, and small pores inside the material open up to allow for more airflow,” he said.
Other materials, he added, sport different stiffness and flexibility levels. By learning a wearer’s body movements and patterns while playing sports, AI could create areas in the garment that are stiffer or more flexible, enabling greater performance. “The possibilities are endless,” Almossawi said.
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