Applying AI for Future Business Models in the Textile and Fashion Value Chain

Abstract

This paper aims to elaborate on the past, present and future application of Artificial Intelligence (AI) in global textile production. For this purpose, leading companies along the entire production chain will be interviewed on the topic using the World Café method at the joint conference of the International Apparel Federation (IAF) and the International Textile Manufacturers Federation (ITMF) 2024 in Samarkand, Uzbekistan. Based on the results, the biggest obstacles to the implementation of AI methods in textile production, the most promising technologies and suitable methods for supporting companies in the implementation of AI methods are empirically derived.

Introduction

The fashion and textile industry faces growing pressure from climate change, resource scarcity, and political demands, yet it lags behind other sectors in digitalization despite contributing 5% of global carbon emissions. Digital business models (DBMs)—business strategies leveraging digital technologies, especially AI—offer a path to sustainable and economic transformation by improving efficiency and profitability across production and administration.

Although AI and digital solutions are widespread in many industries, their adoption in textiles remains limited but is accelerating. Larger companies like Zara use AI for customer data analysis, trend prediction via image recognition on social media, and personalized fashion design, showcasing AI’s potential in meeting modern market demands.

A McKinsey report projects AI could add $13 trillion in value by 2030, revolutionizing business processes much like the steam engine or internet did. However, high implementation costs and job displacement concerns remain challenges.

To assess the status of DBMs in textiles, a World Café workshop was conducted with 33 global industry executives during an ITMF and IAF conference. This participatory discussion explored current use, future outlook, and data requirements of DBMs. The participants represented a broad spectrum of company sizes and geographic regions, mainly from leading textile-exporting countries.

Key findings include:

• While 82% view digitalization as crucial, only about 24% are satisfied with current DBM profitability, indicating early-stage implementation.

• The biggest obstacles are technical complexity and lack of qualified personnel.

• Workforce acceptance is a major barrier, with older employees often resistant to change and concerned about job security.

• Many production sites, especially in low-wage countries, remain poorly digitized, making DBM integration difficult.

• Political pressures, such as the EU’s Digital Product Passport, push companies toward innovation, but entrenched processes and shrinking margins hinder rapid progress.

The study concludes that despite strong awareness and willingness to adopt DBMs, the textile industry’s digital transformation is still in its infancy, mainly due to technical, cultural, and infrastructural challenges.

Conclusion

The importance of implementing digital business models was recognised along the entire textile process chain, regardless of the size of the company. Accordingly, there is great interest in solutions for implementing these models, which allow companies to realise the digital transformation in a timely manner. In this context, companies\' own use of digital business models is perceived as largely inadequate. This discrepancy between reality and their own aspirations can essentially be explained by the lack of qualified personnel and sufficient margins. In addition to these grievances, there are also problems that are specific to the textile industry. Due to the highly fragmented production landscape and the preference for low-wage countries for the construction of factories, the level of digitalisation of textile companies is behind that of other sectors. As a result, many companies do not yet have the necessary digital infrastructure to introduce DBM efficiently. This has created an investment backlog that must first be cleared so that these companies can catch up with current developments. According to a survey in the third World Cafe round, 69.2% of respondents therefore believe that most investments need to be made in technological infrastructure and personnel development in order to enable the implementation of digital business models in textile technology.The future of these models is diverse, but the application in the context of AI and big data is seen as the most important fields. This is largely due to their versatility and media coverage. In addition to the obvious financial motivation to promote the development of new digital technologies, sustainability aspects will also be important for future developments. These developments will be driven forward primarily in cooperation with research institutes and start-ups, as they are in a position to provide the necessary qualified personnel.The World Cafè method has delivered clear and valuable results that allow a variety of conclusions to be drawn. This paper therefore provides a solid basis for collecting further data in this format in the future. On the one hand, the temporal course of the responses can be mapped through the exact repetition of the World Café. This allows trends in this volatile subject area to be scientifically recorded. In addition, participants can be selected more specifically in future. In particular, those responsible for the implementation of DBM and its users could be asked specific questions.

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Copyright

Copyright © 2025 Cedric Heyen, Justin Kuhn, Florian Pohlmeyer, Robert T. Boich, Thomas Gries, Christoph Greb. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.