The fashion industry is going through a digital makeover, and to stay on top, companies are turning to new technologies. One of these technologies that's making waves is generative AI - a fancy term for computer-generated designs. But what does this mean for the fashion industry, and why should we care?

 

In this article, we explore generative AI in fashion. From the basics to current use cases, this article gives you everything you need to know to start leveraging generative AI in your business.

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The Importance of Digital Technologies in Fashion

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In today's digital age, companies across all industries are realising the importance of adopting digital technologies to stay competitive. The fashion industry is no exception. According to a report by McKinsey, fashion companies invested from 1.6% to 1.8% of their income in emerging technologies throughout 2021. This figure is expected to rise to between 3.0% and 3.5% by 2030 demonstrating the increasing importance of digital technologies in the fashion industry. It also showcases their potential to transform the sector.

 

Blockchain, NFTs, and AI technology currently lead the way in the fashion industry. Blockchain technology can provide transparency and authenticity in supply chains, while NFTs are used to verify luxury fashion items and collectibles. AI technology has a broad range of applications in fashion, from product design and virtual try-on to personalised customer experiences, making it a valuable tool for brands seeking to enhance their digital presence.

 

Although still in early development, generative AI is already transforming the fashion industry. With this technology, fashion companies can create unique designs that meet the specific preferences of individual customers, thereby improving customer engagement and satisfaction.

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What is Generative AI?

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Generative AI refers to a type of machine learning technology that can produce unique and novel outputs based on input data. Unlike other types of AI technologies, such as predictive analytics or natural language processing, generative AI does not rely on predefined rules or models.

 

At the heart of generative AI is a neural network that has been trained on a large dataset of input data, such as images or text. The neural network then uses this training to generate new outputs that are similar to, but not identical to, the original dataset. This means that generative AI can be used to create original designs or experiences that are tailored to individual preferences, making it a powerful tool for businesses seeking to engage customers in new and innovative ways.

 

Why is Generative AI Important for Fashion?

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With the potential to transform the way fashion companies approach product design, personalisation, and customer experience, generative AI can disrupt the fashion industry.

 

Instead of relying solely on human designers to create every new design, generative AI algorithms can create unique designs based on input parameters. These parameters can include colour, fabric, style, and a wide range of prompted inputs. This can increase design output and bring new and unique products to market faster.

 

In addition to automating design processes, generative AI also enables greater customisation in fashion. With generative AI, fashion companies can use data-driven insights to better understand customer preferences and create personalised experiences. This can lead to increased customer satisfaction, loyalty, and sales. Furthermore, generative AI can provide fashion companies with a competitive edge by enabling them to tailor their offerings to niche markets and individual customers.

 

The potential impact of generative AI on the fashion industry is already being realised with an expected CAGR of 36.9%. Beyond product design and personalisation, generative AI can revolutionise supply chain management by improving production efficiency, reducing waste, and increasing transparency.

 

However, implementing generative AI in fashion is not without its challenges. Fashion companies need to have specialised skills and knowledge to adopt and integrate this technology effectively. 

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Use Cases for Generative AI in Fashion

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Generative AI has already shown significant promise in revolutionising the fashion industry, and it has many potential use cases. Some of the most promising use cases for generative AI in fashion include product design, forecasting trends, and improving supply chain management. Beyond these business-facing use cases, Aistetic continues pushing the possibilities of generative AI for customer-facing use cases. These use cases include virtual product try-ons and demos as well as intelligent AI agents and self-service.

 

AI Agents and Self-Service

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Another relevant use case for generative AI in fashion is intelligent AI agents and self-service. With this technology, fashion companies can provide their customers with personalised product recommendations and customised styling advice.

 

These AI agents can communicate with customers through chatbots or voice assistants. They can provide customers with relevant product information and personalised recommendations based on their preferences and previous purchase history. This can significantly improve customer satisfaction and increase sales. With personalised recommendations and immediate customer service, customers become more likely to make a purchase. One McKinsey report found that personalisation drives a 10 to 15% increase in revenue.

 

Recently, Zalando launched its own AI fashion assistant using ChatGPT. It provides personalised recommendations and styling advice to customers. This enhances the customer experience and drives sales.

 

Kering also joined this trend with its recent launch of an experimental website called KNXT. This experimental website uses an AI-powered chatbot named /madeline as a personal shopper for customers. As the first personal shopper of its kind, /madeline provides personalised product recommendations and styling advice to customers looking to purchase items from any of the group's brands.

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Virtual Try-Ons and Demos

 

Virtual product try-ons and demos can significantly enhance the customer experience. It allows shoppers to visualise how a particular piece of clothing or accessory would look on them without physically trying it on.

 

Through generative AI, fashion companies can create realistic and personalised virtual representations of their products. This technology enables customers to virtually try on clothing and accessories using a digital avatar that matches their body type, size, and skin tone.

 

Accurate virtual try on technology provides customers with a better understanding of how the product looks and fits before making a purchase. Providing this service can help reduce or eliminate the 70% of returns in the fashion industry caused by a poor fit or style.

 

Conclusion

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If used effectively, generative AI can revolutionise the fashion industry. It offers solutions to the most pressing challenges currently facing the fashion industry such as the large percentage of returns due to a poor fit or style. The fashion industry can also leverage it to create highly effective AI agents and self-service customer support.

 

At Aistetic, we are committed to staying at the forefront of generative AI technology in the fashion industry. Our team of experts delivers the expertise to enable leaders in the fashion industry to fully utilise the power of generative AI. Please book a meeting with one of our product specialists today to see how generative AI can help your business thrive.