The fashion industry is dynamic and has a long-standing relationship with technology. In more ways than one, the fashion industry relies on AI and Machine learning to develop better trend analytics and matching algorithms to develop more market-driven designs. This has led to a revolution in the utility of technology to create more remarkable experiences. Fashion is evolving with the help of technology, and AI is leading the way in its endeavor.
Here are 5 key areas where AI is bringing innovation to the fashion industry –
1. Automating the design process.
Amazon built an AI designer a few years ago, in the hopes of reaching a leverageable point in the industry. It built the core algorithm to create better trend forecasting and revealing new insights that human designers couldn’t. It was one of the first few attempts at replicating creativity, through iterative processing and deeper learning. It used a novel approach called generative adversarial network (GAN).
AI can help in making the design process more streamlined through technology. It can repeatedly make multiple mistakes per second and review customer feedback to analyze new trends. While the process is resource intensive, it can uncover hidden insights within the industry.
“AI can assist design teams by enhancing and reducing overall lead times and expand their creative discovery by analyzing and remembering insights from thousands of images and videos using computer vision. It’s about reducing a time-consuming, resource intensive, manual process, or blowing up that research element by providing access to much wider sources than ever before.” - Zarine Bajaj, Findow (AI fashion tech)
With the smart TV, smart mirror, and smartwatch movements, we’ve reached a point where AI can make everything smarter. This takes the physical realm and brings it to life using digital technologies. It also enables greater integration within the fashion community, by bringing new designs to connected audiences.
By connecting technology to interactive design, companies can make fashion more accessible. A smart mirror can make better suggestions that depend on immediate feedback from the person in front of them. The algorithm can learn about soft areas like “taste” and “preferences” from a digital perspective.
3. Better trends analysis
Research from IBM showed that 52% of female Gen Z shoppers want to see tools that enable greater customization. This spurred them to work with Tommy Hilfiger to design better customization tools for apparel choices. Designers could come up with new ideas using data obtained from millions of apparel images. AI enabled them to create new designs that were more personalized and market-oriented.
“The machine learning analysis gave us insights about the Tommy Hilfiger colors, silhouettes and prints that we couldn't begin to consume or understand with the human mind. This enabled the FIT Fashion Design students to take their inspiration from Americana or popular fashion trends and marry that with the ‘DNA’, if you will, of the Tommy Hilfiger brand across those dimensions to create wholly new design concepts.” - Michael Ferraro, executive director FIT’s Infor Design and Tech Lab.
4. Capturing forgery & plagiarism
Forged designs or copied apparel pieces can be caught at scale using AI. The core technology can enable designers to copyright and review another artist’s work. Forgery can be detected across various e-commerce sites at scale, allowing the original artists more leverage to claim a particular design.
AI can also create efficiencies in the detection of fake goods being present in the market. Through the image recognition and automated tracking features available in the market, it can dissuade companies from copying designs. This has a net-positive impact in the fashion domain holistically.