The revenues of the fashion sector in the global market are expected to meet $2.25 trillion by 2025. The fashion sector is undoubtedly one of the largest industries worldwide. Due to its characteristic of fast-changing, fashion designers and brands started utilising AI tools to surpass design and manufacturing limitations. Technology becomes the crucial element in the fashion industry to ensure stable, fast production and sustain the brands' position in the highly competitive industry.
Prediction of fashion trend
Fashion brands use machine learning to predict what customers will want to wear in the following fashion season. By predicting customers' preferences, fashion brands can adjust their current approach to product design and development to cope with the demand in the future. Therefore, the fashion industry can practice a better and more efficient allocation of resources, leading to more desirable productivity and results.
In the traditional approach, the forecast of fashion trends is typically labor-intensive, consisting of observation and data collection from designers and influencers in the fashion industry. The conventional method involves only the participation of personnel in the industry, but not the fashion consumers. The fashion preferences of the designers do not equal the actual demand from the customers. This method, therefore, does not guarantee high accuracy in the prediction.
In contrast, the forecast of fashion trends is data-driven, and the data used is collected directly from the fashion customers. The fashion brands gather customer's data from various channels. The most common medium is their mobile shopping sites and apps, where the brands can collect data such as customers' personal information and purchase records. The massive amount of data is then passed to the AI for analysis. By machine learning, the fashion brand can manipulate the intensive amount of data and predict future trends from data. The prediction helps fashion brands plan the styles and quantities to manufacture, achieving a better resource allocation in the fashion brands. Besides, the brands are using this technique to manage inventory and make business decisions.
As mentioned, the fashion sector is one of the biggest industries in the world. At the same time, it is one of the most polluting industries. Some pioneers wish to change the situation by introducing and promoting eco-friendly and sustainable fashion, considered "Digital Fashion".
In the concept of "Digital Fashion", the customers buy digital clothes for their online persona on social media. The customers will never receive the fashion items in person because the items will never be manufactured physically. Digital Fashion aims to create online interactive fashion experiences with customers while reducing textile waste.
One of the experimental technology in Digital Fashion is the virtual model. Virtual models help designers to demonstrate their latest creations around the world online. The designer will never make the clothes physically. Hence, it makes fashion more sustainable. The first digital model, Shudu Gram, has successfully owned 218k followers on Instagram. Designers put their latest designs on Shudu and showcase them on social media. Many said they did not realize that Shudu was not an actual human by browsing the photos online. Shudu has gained attention from fashion enthusiasts. The awareness gained from fashion enthusiasts indicates the potential of virtual models in the fashion industry.
Automated quality inspection
In the fashion industry, AI is already in use in the manufacturing process of the garment. The manufacturers are using automated quality inspection to promote productivity, efficiency and reduced costs. The technique is enabled by computer vision and machine learning.
Using this technique in the garment production line helps manufacturers keep track of the number of produced garments and check for each surface defeat. The exact number of garments being built is shown on the dashboard of the system.
On the factory level, this system allows the manufacturers to effortlessly switch the current garment to work on several times a day, without any workflow changes. It helps the garment suppliers counteract delays in the fabrication process. Moreover, the system increases transparency in the production process for all stakeholders with real-time reporting on the number of finished garments.
Three AI And Tech Trends That Will Transform The Fashion Industry (forbes.com)
Fast Fashion Counts on AI and ML | insight.tech
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