Fashion can be fun, whether you’re looking for sales, scrolling social media to see the latest trends, or choosing outfits for your vacation. Both the retailer and the shopper can find it frustrating (fit! It can also be very harmful to the environment (most clothing returned ends up in a landfill).
TOP 5 uses for AI in fashion
- Trend forecasting
- Sizing more accurately and with a better fit
- To prevent counterfeits, authenticate items
- Streamlining manufacturing
- Reduce returns
Artificial Intelligence in Fashion
Nearly all parties involved in the fashion industry solve these problems with AI. Both customers and manufacturers can use applications to determine the right fit, which makes shoppers happier and helps reduce the industry’s environmental impact. AI is used by designers to design fabrics and garments. Consulting firms use it for forecasting trends for manufacturing clients.
Data collection is the key to unlocking the secrets of magic. Data collection is key to unlocking the secrets of authenticating high-end items like Birkin bags, Cartier watches, and Birkin handbags. AI can gather, process, and draw insights out of all kinds of data, including social media images and bodily functions like heart rate and sweat.
“We are in the very early stages of this. It’s already mind-blowing. Said Hussain Almossawi is a designer, and CGI (computer-generated imagery) artist, both based in New York City.
“If this tells us anything it is that there are many more to come. Machine Learning is all about taking in data and learning from it, then giving us an output that’s based on what we are searching for.
Also read: Top 12 AI Chatbots for Business in 2022
7 Examples and Applications for AI in Fashion
Let’s now look at how AI can make fashion more intelligent and sustainable.
AI can Fix Fit
Improper fit is the most common reason to return clothes purchased online. Returns can cost retailers up to 38% of the original price. Carlanda McKinney is the founder and CEO at Bodify, an Overland Park Kansas-based startup dedicated to helping solve the fit issue.
Bodify takes photos from customers and then uses computer vision for their measurements. Machine learning compares the measured data with the company’s stored data. Shoppers will receive a list of brands that are right for them. McKinney stated, “You’ll find these brands that you didn’t know existed.”
Bodyfit’s data can be used to help manufacturers cut garments to fit individuals, coordinate sizes between different types of garments (such as shirts and jeans), and decide the best place to make their garments. McKinney stated that the same pair of jeans can also be made in China or Indonesia and will fit differently.
Fit for Everybody is a startup located in Princeton, New Jersey. It provides shoppers with a video showing them where they should measure themselves. The data is used by Fit for Everybody’s designers to create patterns that are more closely aligned with customers’ measurements. Laura Zwanziger (founder and CEO) stated that you are basically creating clusters. She is making five sizes that will cover as many people as possible. The goal is to optimize every cluster.
Manufacturers will be able to use Fit for Everyone’s data to improve consistency in grading. This refers to the process of sizing up or down from the fit model. Zwanziger stated, “I want it to be seen by them as a product that makes life easier.”
AI Helps to Make Decisions
Is this color good for me? Customers can be helped by retailers using AI-powered virtual styling tools that help customers choose the right products for their body, skin tone, and apparel needs.
Styleriser is a B2B German company that makes software that uses AI for image consulting. The online retailer allows customers to upload their photos and a virtual stylist will analyze them. The tool recommends the most flattering colors for each person and gives specific recommendations (e.g., wear cream instead of white or charcoal gray instead of black).
Mark Hunsmann, CEO and co-founder, stated that the tool increases confidence in shopping which, in turn, leads to a higher purchasing readiness of 80 percent. He also said that this means there are fewer returns which helps to sustain the industry.
AI Helps Designers
Almossawi uses AI to inspire and generate ideas. It has helped him come up with more than he could do without it. The early stages of any designer’s process involve a lot more explorations and ideas sessions.
These include brainstorming with colleagues or bouncing around with blue-sky ideas. He said that AI aids collaboration by expanding person-to-person and human-to–machine collaboration. “AI is still very young, as crazy and fascinating as it may sound. He said that he could see the program improving and going beyond just putting out images.
Almossawi created a line of garments using AI based on the Japanese Kimono as an example. He stated, “I thought it would be cool to look into designing other silhouettes with different textures and details.”
AI Aids Merchandising
Augmented and virtual reality (AR) are AI-driven tools that help online shoppers better understand what a garment looks like and how it will fit them. According to Fashionista, certain apps allow customers to project garments onto real bodies and then play with texture, color, and accessories to create the perfect look.
Almossawi stated that AI can place products in the right environments. He said that product placement is an important part of creating hype about a product and telling the story of why it was created. AI can quickly create cool backgrounds in different styles for your product.
AI CAN “Green Fashion”
In the fashion trade, green is the new black, since apparel manufacturing contributes to as much as 8 percent of global greenhouse gas emissions and as many as 9 percent of annual microplastics that end up in the oceans according to the UN Alliance for Sustainable Fashion. Nearly all returned items end up in a landfill because restocking returns can be costly for retailers, and high-fashion brands don’t want to lose their brand value by selling to discounters.
AI can be used to help with trend forecasting and many other areas. It is not easy to decide what customers want and then mass produces that item. A bad decision could result in a lot of unsold clothing. Many firms use machine learning and AI to analyze social media images, taking note of prints, shapes, and colors, to help their clients as manufacturers figure out which items will sail and which ones will sink. These companies also use AI to help brands determine pricing strategies and avoid trends that are going out of fashion.
AI Can Reduce Counterfeiting
A fake Birkin bag is a desirable purchase. No one, even if they’ve paid at least $40,000 gets the real deal. These embarrassing moments can be prevented by two applications of AI.
An AI-based tool developed by the accounting giant Deloitte to spot design infractions. Dupe Killer is a tool that uses millions of photos to identify subtle design elements. It can detect the shape and color of items, as well as unique stitching patterns. Dupe Killer is a tool that helps brands identify and pursue companies that are illegally using their trademarks.
According to The Tech Fashionista, another solution is computer vision. This field of AI allows computers to identify “real” items, helping customs officials spot counterfeits.
AI Can Advance Wearables
AI-powered wearable devices, such as fitness band that tracks heart rate, motion, and performance, are already available on the market. According to digital transformation company, eInfochips, it’s a huge market, with sales of $42.4 million by 2023.
Designer Hussain Almossawi predicts that this will extend to apparel. He said that AI could be integrated into clothing to create smarter fabrics, better clothes for sports and performance, as well as clothes that are more responsive to the body. He said that materials can detect when the body is hot and/or sweaty, and tiny pores within the fabric open up to allow more airflow.
He said that different materials have different levels of stiffness and flexibility. AI can create stiffer and more flexible areas of clothing by learning the wearer’s movements and patterns during sports. This will allow for greater performance. Almossawi stated that there are many possibilities.