5 Ways Artificial Intelligence is used in the Fashion Industry

Fashion and AI

Published by FirstAlign

Clothes define us. It is who we are – a statement, a lifestyle choice. With clothing, comes it’s share of challenges. The Fashion Industry needs to design and produce products for different people. People from different regions and cultures. Can Artificial Intelligence in Fashion improve the services of the industry?

Fashion for the 21st century

A digital era needs FashTech. Digital technology is disrupting traditional shopping methods. FashTech is about the adoption of technology and innovations in Fashion. Fashion and Artificial Intelligence (AI)is now becoming a realistic combination.

Why Artificial Intelligence for fashion?

  • Challenging Customers! Customers now want products for their specific needs. They want clothes personalized for their style, body, and tastes.
  • The modern shopper is TechSavy, with technology on the go anytime and everywhere. Shopping is now just a click away. Products are reviewed online and news sentiment spreads quickly. Fashion influencers are rapidly changing people’s choices.
  • Global environmental concerns are forcing a shift towards sustainability. Reducing water consumption, and efficient use of energy has become the top priority.

5 ways AI is used in the Fashion Industry

AI in design and development

In 2018, the Fashion Institute of Technology (FIT), IBM, and Tommy Hilfiger collaborated to study 15,000 Tommy Hilfiger images. They also analyzed 600,000 publicly available runway images. The aim was to understand silhouettes, colors, and styles.

IBM’s AI for fashion capabilities is a suite of application programming interfaces (APIs). It is developed and trained for the fashion industry. It uses Deep Learning, Natural Language Processing, and computer vision to improve operations. AI solutions improve customer experience while enhancing product design and development.

Zolando, an online retailer in Europe and the UK is developing software for designers. One of Zolando’ AI solutions for fashion is to provide better personalization of fit. The key challenge was that individuals had only a handful of products in their sale history. To alleviate this, they developed models that can leverage size, and fit relevant information. They developed models across individual customers to improve personalized recommendations.

They did this by developing a unified mapping scheme. It allows for both customers and articles to be implicitly projected and compared in a semantic-free (latent) feature space. They used Bayesian modeling as well as Deep Learning for this project. Bayesian theory provides a principled framework. A framework combining beliefs about missing or sparse information with noisy observations.

Trend Forecasting

Artificial Intelligence collects, analyses, and interprets data to predict future trends in fashion. Data is collected from social media, e-commerce platforms, and runways. This information is combined with historic data to forecast the optimum product. Products that resonate with the customer base.

Heuritech, a fashion technology company offers predictive analytics on trends and products. They apply their computer vision technology to millions of images on social media. They analyze millions of images each day and identify trends in detail. Then using machine learning algorithms, they predict fashion trends in advance.

Online product recommendations

Artificial Intelligence uses visual detection and key product attributes to recommend alternative products. When a product goes out of stock, AI recommends different relevant products on the website. Such recommendations increase customer engagement and reduce sales opportunities lost to competitors.

Finery, a wardrobe management application determines what apparel is already in the user’s wardrobe. It asks for a users email address and permission to access email receipts of fashion purchases. Using this data, Finery’s AI algorithm suggests looks using existing clothing items. It also recommends clothing that could match the user’s current style.

AI for Personalization

Research says that 80% of consumers are more likely to buy when brands offer a personalized experience. With this statistic, it is clear that customer personalization is a top priority. Machine Learning and AI recommends personalized products to the customer. It considers their body type, color, occasions, and individual style preferences.

Woodhouse Clothing, a men’s online fashion retailer, offers AI-based personalization. Nosto, a growing e-commerce personalization and retail AI platform developed Woodhouse’s technology. It uses ML algorithms and other statistical techniques to predict. It analyses data to identify commonly bought or browsed items. Based on which Nosto’s platform automatically displays the most relevant cross-selling recommendations. It recommends personalized clothing to visitors based on brand, style, and product preferences. For new visitors, it recommends products based on real-time bestsellers.

Digital In-Store Experience

Digital In-store experience powered by AI is futuristic and provides one of a kind shopping experience. AI-powered smart mirrors provide virtual visualization of clothes. You can see the way you would look even without trying on the clothes.

For such smart mirrors, clothing racks are RFID (Radio-frequency identification) enabled. They also use gyro-sensors and Bluetooth low-energy chips. Together they show the item selected by the customer automatically on the mirror.


The world of fashion is fast-moving. And buyers and designers are in a constant chase to catch up with the latest trends. To stay relevant and visible, the Fashion Industry is adopting technology in many ways. Some biggest names in the Fashion Industry like H&M and Tommy Hilfiger are now heavily investing in Artificial Intelligence. AI is now used in online stores for personalization, recommendation, and trend forecasting. Though AI for fashion is widely used in online stores, in-store AI is yet to be fully realized. The futuristic in-store AI shopping experience that we are all looking forward to.


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