The Latest AI Trends in Fashion

November 16, 2022
Zarina Gareth, Guest Author

Brands need to keep up with the latest artificial intelligence (AI) technologies to stay relevant and powerful in the fast-paced world of fashion. IndustryWired reports that the global spending of the fashion and retail industry on AI technologies will reach US$ 7.3 billion by the end of 2022 due to its important role in product innovation. After all, big brands in the industry heavily rely on AI to improve their products and services. One of these businesses is the French luxury brand Dior, which invested in an AI beauty assistant who can answer the questions of online consumers.

Apparel brands are increasing their spending on AI investments due to the recent innovations that can be useful for designing and customer relationship management. Let’s take a look at the latest AI trends in the fashion industry:

Multiple AI Technologies for Customer Service

Much like Dior, brands are starting to leverage multiple AI technologies to improve their customer service.
Chatbots are one of the most common uses of AI, and TechTarget explains that this innovation allows companies to answer questions or update clients regarding their own deliveries. However, conversations on chatbots can get quite heated from time to time, which is why businesses also use sentiment and advanced analytics to recognize when a customer may be upset about their order. By combining these technologies, fashion brands can quickly de-escalate situations and increase the satisfaction of their customers.

H&M chatbot
Client Personalization through Self-Learning Systems

Brands don’t always nail the designs that consumers want. To make sure that they hit the mark, more businesses leverage AI in discovering the possible styles, fabrics, and cuts that their audience prefers.
The innovation involved in this process is a self-learning system, which studies certain aspects through trial and error from specific examples. Our article entitled How Do Self-Learning Systems Work explains that numerous fashion brands leverage this AI technology to stay relevant in the highly competitive industry. This technology uses big data, client personalization, and other services to study the preferences of consumers so that it can generate more custom and personalized styles that align with the audiences’ tastes.

Generative Adversarial Network in Apparel Designing

It’s difficult to come up with fresh ideas when there are numerous clothes, accessories, and shoes in the market.
As such, many fashion brands start using AI to help their designers discover new styles. Maryville University outlines how AI advancements are transforming future workplaces, and this is especially true in the fashion industry. Generative Adversarial Network (GAN) is one of the latest AI innovations in the fashion industry because it can distribute data, generate data sets, and improve outputs through two competing neural networks. By training these neural networks, AI can generate realistic images of clothing and even edit design concepts to help brands produce new styles.

Real clothing vs GAN
Side-by-Side Comparison of Real Clothing and Generated Clothing
AI Systems for Data-Based Decision-Making

Every decision counts in the industry, whether it’s about the colorway of a design or the global expansion of a brand.
Fashion businesses try to simplify this process by using AI systems to make decisions based on data. Researchers from the Aristotle University of Thessaloniki explain that brands can retrieve data from company databases and online sources through dictionary mapping and natural language processing techniques. Once these data sets are retrieved, the AI system can use machine-learning techniques like prediction models and recommender systems to suggest the best products or even the most appropriate moves based on each designer’s goals.
It's clear that AI technologies are a must-have for fashion brands that want to rise above competition. By investing in the latest AI trends, apparel businesses can create innovative designs and build better relationships with their consumers.  

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Written by Zarina Gareth


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