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Artificial intelligence on fashion and textiles in 2023

Published: 2023-05-26

Artificial intelligence (AI) has been making waves in the fashion and textiles industry in recent years, and 2023 promises to be no different. From designing and manufacturing to marketing and customer service, AI is revolutionizing the way businesses in this sector operate. This is substantiated by popular fashion brands like Zara, H&M, Dior, Macy’s, and Nike, who all use AI in their business models. Whether through AI chatbots, personalization, or trend forecasting, AI is already helping both small and big fashion companies promote goods, ameliorate deals, and enhance the client experience.

Figure: AI-Generated Fashion designs.

Design and manufacturing

AI can assist designers in creating new designs and improving existing ones. For example, AI can analyze customer data and generate personalized designs based on their preferences. AI can also help designers identify trends, optimize patterns, and generate 3D models of garments.

AI can improve production efficiency and reduce waste in the textile manufacturing process. AI can monitor production lines and identify defects, predict machine breakdowns, and optimize production schedules. This can lead to faster production times, lower costs and fewer errors.

“AI and machine learning can be used within textile machinery to make sure pieces of apparel or other goods are cut correctly so little to no fabric is wasted,” said Jeffrey Joines, Department head of textile engineering, chemistry, and science at North Carolina State University Wilson College of Textiles.

Color matching and dye formulation

Using AI for color matching and dye formulation is to train machine learning models on large datasets of color and dye information. These models can be used to predict the optimal dye formulations for a given fabric, based on its material and desired color. This can help to reduce the time and cost required for manual dye formulation and color matching. 

Another approach is to use computer vision techniques to analyze images of fabrics and identify their color characteristics. This can be useful for color matching, as it allows designers and manufacturers to identify the exact color of a sample and find matching fabrics or dyes. Additionally, these techniques can be used to create digital color libraries, which can be used to improve color accuracy and consistency across different stages of production.

AI predicted fashion trends for 2023

AI is revolutionizing the fashion industry by impacting all aspects of the supply chain and retail operations, including product development and design. Now, AI is taking things to the next level by actually designing clothing that could take the world by storm. These AI-predicted fashion trends for 2023 include a mix of futuristic and magical styles, such as Hopecore, which features bright colors and a calming feel. The implications of AI in fashion extend beyond just predicting fashion trends, and it remains to be seen what other insights AI will reveal in the future.

Market size

AI In Fashion Global Market Report 2023 – by The Business Research Company says, The growth of the global AI in the fashion market from $0.65 billion in 2022 to $0.91 billion in 2023, with a compound annual growth rate of 40.0%.

Additionally, Price Waterhouse Coopers (PWC) has predicted that AI will contribute nearly $16 trillion in value to the global economy by 2030.

Managing quality control

AI for quality control is to use machine learning models to analyze images of products and identify defects. These models can be trained on large datasets of images, allowing them to identify common defects and anomalies with a high degree of accuracy. For example, a machine learning model could be trained to identify stitching errors or fabric defects.

Fabric defect detection with cartoon–texture decomposition

This method decomposes the fabric image into two components: the cartoon component and the texture component. The cartoon component represents the smooth regions of the fabric, while the texture component represents the unstable regions of the fabric, such as defects. The cartoon texture decomposition method uses a low-pass filter to extract the cartoon component, which is then subtracted from the original image to obtain the texture component. The texture component is then thresholded to identify defects, which can be classified based on their size, shape, and intensity. 


AI can be used to optimize production processes and reduce waste, helping to make the textile industry more sustainable. For example, AI algorithms can identify the most sustainable materials and help reduce the environmental impact of textile production.

“AI will be an essential tool for H&M Group to reach our vision of achieving a climate-positive value chain by 2040,” said Linda Leopold, Head of Responsible AI & Data at H&M Group.

Artificial intelligence (AI) has the potential to revolutionize the fashion and textile industry in a number of ways. From improving design and product development to streamlining the supply chain and logistics to enhancing marketing and customer experience, AI is transforming the industry in significant ways. As we move into 2023, we can expect to see continued growth in the use of AI in this sector. With the ability to improve efficiency, reduce waste, and create more sustainable products, AI is poised to make a significant impact on the fashion and textiles industry for years to come.