Artificial intelligence and sustainability in the textile industry

The textile and fashion industry outlook is deeply intertwined with the dual transitions of digitalization and sustainability. By integrating digital tools with sustainable practices, businesses are not only minimizing their environmental impact but also boosting efficiency and fostering innovation.

 

AI is emerging as a crucial catalyst, promising to enhance sustainability in the textile and fashion industry through various contributions. It aids in optimizing processes, reducing waste, improving resource management, increasing product longevity and engaging consumers more effectively. By harnessing AI, the industry can not only achieve environmental goals but also gain greater efficiency and customer interaction, paving the way for more sustainable consumption patterns.

 

Let's explore how AI is influencing the textile and fashion industry, while also considering the associated risks. 

 

Among the more promising AI applications are those in the fields of design assistance, creativity enhancement, production and supply chain optimization, as well as a better understanding of consumer behavior. Here are a few potential application examples.

• Prototyping that doesn't use raw materials, energy or water, and doesn't generate waste to produce test samples and collections for customer presentation is on the horizon thanks to the ability of generative AI to digitally assess the fit, look, and functionality of fabrics (knitted or orthogonal) and garments before they are physically produced, allowing a reduction in waste of materials as well as time. This includes 3D views and 3D simulations of the draping of fabrics in a garment, as well as the appearance of fabrics or accessories in various colors. This process, which also involves sharing projects and receiving real-time feedback from buyers and retailers, was once only imaginable. However, such advancements are expected to become a reality in the next few years, transforming how we create and refine products in a sustainable, efficient manner.
• AI algorithms could help the reuse of cutting scraps, by repurposing existing clothing or textile waste and by suggesting newer ways to reuse certain cutting waste within the company production – e.g. after training with all the patterns and designs produced by the company - thereby facilitating the implementation of circular economy practices.
• A large number of applications are being developed for supply chain optimization, inventory management, and complex logistics issues. AI's capacity to find hidden patterns in large volumes of data from different stages of the supply chain can provide solutions focused on minimizing waste generation and saving in emissions.
• While fashion forecast remains a complex challenge, AI can assist in analyzing consumer behaviour, feedback, and usage patterns, and provide insights into product durability, quality, and potential areas of improvement. This knowledge can be used to design more durable and sustainable products, reducing the need for frequent replacements and minimizing waste.

These advancements are not without their challenges. Reliance on AI can lead to job displacement. Moreover, the use of AI demands vast amounts of data, raising concerns about privacy and security. Additionally, the algorithms themselves can sometimes perpetuate biases or stifle innovation by repeating proven patterns, if they are not carefully monitored and adjusted.

Acknowledging these risks is essential as we leverage AI's potential to achieve sustainability goals in the fashion industry.