Much of the world is switching to a digitally transformed strategy and the fashion industry is no exception. The 2023 Digital Business Study shows that 93% of companies are going digital in their operations. According to McKinsey, fashion brands and companies invested approximately 1.7% of their income in 2021 on emerging technologies like generative AI and this is estimated to rise to 3.0%-3.5% by 2030. 

Generative AI transforms the creative process by providing designers with methods to generate new concepts, patterns, and styles. Using large datasets of existing designs and patterns, it identifies common elements and characteristics. After learning these patterns, the algorithm can generate new designs that incorporate these elements uniquely and innovatively.

Generative AI brings certain benefits to fashion, let’s examine them.

What does Generative AI bring to the Fashion Industry?

Generative AI is disrupting the fashion industry in exciting and innovative ways. From virtual try-on technologies to customized production, AI is making waves and helping companies stay competitive. 


With AI technology, automating repetitive and time-consuming tasks can significantly benefit the fashion retail industry. The growing field of generative AI is adding more value to the fashion industry through the tagging and categorization of products, the management of inventory, and the ability of employees to focus on more important activities, such as customer service.


Historically, the fashion industry has contributed significantly to global waste problems by polluting the world with textile waste. This can be offset by generative AI techniques that analyze historical data to identify and recommend sustainable and eco-friendly materials, processes, and practices. A few of these materials can be recycled or biodegradable, while others can be made with more energy-efficient production processes that reduce waste and emissions.

Virtual Try-on and Augmented Reality

As part of its augmented reality (AR) initiative, luxury brand Cartier has introduced a virtual ring fitting system, allowing users to try rings without purchasing them.

The Cartier Retail Innovation Lab in Brooklyn developed the technology using generative artificial intelligence. With virtual try-on technology, customers can virtually try on clothes and accessories without having to physically wear them. They can see how a product will look on them in real-time by uploading a photo or using their device’s camera. This dramatically improves customer engagement and satisfaction and can influence purchases.

Customization at scale

Generative AI can enable companies to manufacture products tailored to each customer’s unique needs and preferences by generating designs and patterns based on algorithms. Moreover, generative AI can make customized fashion recommendations based on a customer’s style preferences, body type, and past purchases. Customers can enjoy a more curated shopping experience.

5 use Cases of Generative AI in the Fashion Industry

1.Creative Designing for Fashion Designers

Generative AI can help fashion designers in the creative design process by coming up with fresh ideas or by improving and modernizing current designs following the newest trends thanks to its excellent ability to produce new visuals and information. Several methods, such as the following, can be used to accomplish this:

  • Generate design: Based on predetermined constraints and parameters, such as the desired aesthetic, materials, and target market, generative AI can produce completely original fashion designs.
  • Style transfer: Designers can build variants on existing designs or integrate parts from other sources by using generative AI to adapt the style of one design to another.

2. Turning Sketches into Color Images

The fashion sector benefits from generative AI since it can also turn sketches into fully colored visuals. Generative artificial intelligence allows designers and artists to experience their vision in real time. 

Additionally, generative AI can reduce human error, such as pattern and color-matching mistakes. Further, it can help fashion firms be more inventive by allowing them to analyze many sketch-to-color combinations and produce various alternatives for evaluation.

As an illustration, Khroma technology enables a trained algorithm to produce accurate and unique color palettes. Similar to this, Colormind allows you to create original color palettes based on your favorite images from movies, photos, artwork, etc.

In addition, generative AI can save time and resources by reducing the need for physical samples.

3. Generating Representative Fashion Models

Fashion brands can serve a wider spectrum of clients more effectively and exhibit their products more accurately and realistically by using generative AI to build a variety of fashion models. 

There are numerous methods to use to produce a variety of fashion models:

  • Virtual try-on: With the help of generative AI, shoppers may digitally “try on” clothing by overlaying synthetic fashion product representations over photographs of real people. Customers can view how the garments would appear on them individually by customizing these virtual models to represent a wide range of body types, colors, and sizes.
  • 3D rendering: Generative AI can produce 3D models of clothing items that can be rotated and viewed from various perspectives. To help designers see how their designs would look on various body kinds, colors, and sizes, these models can be altered to reflect a wide variety of body types, colors, and sizes.

Another digital startup, Lalaland, creates incredibly lifelike virtual fashion models for e-commerce platforms. These models are powered by generative AI. It functions by establishing model avatars, inputting garment photographs, styling the merchandise, and then downloading output images.

4. Marketing & Trend Analysis for Fashion Brands

Companies may accelerate and enhance their trend-forecasting and marketing analytics capabilities with the help of AI-powered generative models. Companies can better anticipate trends and better serve customers’ future demands as a result.

Generative AI helps Combine several techniques, including machine learning and probabilistic programming. Powerful generative models that take into account the needs of the customer are made possible by these techniques in the fashion industry.

Additionally, generative AI can increase your customer reach and market share by creating a highly customized and personalized product range for the new target markets using data analysis, natural language processing, and machine learning.

5. Protecting the Data Privacy of Consumers

Generative AI is used in the fashion industry to enhance customer data privacy. Using generative AI algorithms, fashion companies can create new designs while protecting client information. The synthetic datasets generated by generative AI can be used to develop distinctive patterns and automated data analytics, including:

  • contact details  
  • financial details 
  • shopping history 

As a result, business insights into target markets can be gleaned while protecting the financial security and privacy of an individual. As a result, generative AI allows fashion firms to revolutionize their business models safely. 

Future Of Generative AI In Fashion

Generative AI is undoubtedly transforming the way the fashion industry operates and innovates. As technology advances, we may anticipate seeing more companies use generative AI to produce novel designs, patterns, and styles as well as to improve the sustainability and efficiency of businesses. Despite the challenges associated with copyright for AI-generated work, ownership issues about whether the fashion designer or the AI programmer deserves authorship rights for the work produced or the potential for diminishing human creativity in the fashion industry leading to unemployment, the future of generative AI in the fashion industry is promising, and we can’t wait to see what comes next.



Edited By – Naga Vydyanathan