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Most people have gone through the moment of staring at a closet full of clothes yet feeling like they have no outfits to wear. Individuals in developed countries own many pieces of clothing, partially due to fast-fashion social media trends, which causes great harm to the environment. These problems of the overwhelming choice of possible outfits to create from your garments and many aspects of unsustainability in the fashion industry are both addressed by Salon, an AI personal stylist platform which promotes circular fashion.

The problem: environmental harm and an overwhelming number of choices to make

The number of times pieces of clothing are worn has decreased by 35% over the last fifteen years (Nizzoli, 2022). On top of that, people buy 60% more clothes than in the year 2000 (Igini, 2024). As a result of this, individuals throw away quite a few of their clothes every year, which mostly end up in landfills and lead to environmental pollution (KEMI Swedish Chemicals Agency, 2014). At the same time, owning many garments creates an overwhelming amount of outfit choices (Schwartz, 2015).

The solution: Salon

To help mitigate this global problem, Salon’s mission is to increase wear per garment and discourage unnecessary purchases in a unique way by changing the behaviour of individuals. By using Salon, users get a digital version of their wardrobe, an AI-powered personal stylist, virtual try-ons, a fashion community, and a (second-hand) marketplace all in one platform. With these features, the platform addresses both the fast-fashion crisis and the daily challenge of selecting an outfit through an AI-powered fashion ecosystem that transforms the way users engage with their existing wardrobe and promotes sustainable consumption. This approach is in line with the United Nation’s Sustainable Development Goal 12 of Responsible Consumption and Production. Salon specifically focuses on responsible consumption by aiming to reduce waste by extending the lifespan of clothes through smart styling and increased reuse of garments. This will be done by shifting consumer behavior by encouraging people to be more resourceful with their existing wardrobe, instead of frequently purchasing new clothes.

Market fit

Salon operates at the intersection of fashion technology and environmental sustainability. These markets were valued in 2024 at 239 billion USD and 10 billion USD respectively, at compound annual growth rates of 6.3% and 9.5%. Its primary target demographic is Generation Z because they are relatively seen as the most active in these markets. They are “technologically native” (Mehta, 2022), fashion-focused, and environmentally aware. However, they experience an attitude-behaviour gap between their vision on sustainability and their actual fashion purchasing habits (Prashar & Kaushal, 2025). Salon bridges this gap by merging environmental sustainability and consumer convenience with its AI-driven services. This intersection of these markets highlights a significant societal and commercial opportunity.

Conclusion

Salon demonstrates how GenAI can transform fashion consumption from frequent purchasing and waste of clothes to mindful styling with sustainability in mind. By turning wardrobe management into a digital ecosystem built on the principles of sustainable consumption and user convenience.

References

Igini, M. (2024, May 30). 10 concerning fast fashion waste Statistics. Earth.Org.

KEMI Swedish Chemicals Agency. (2014). Chemicals in textiles – risks to human health and

the environment. In KEMI Swedish Chemicals Agency (No. 6/14). https://www.kemi.se/en/publications/reports/2014/report-6-14-chemicals-in-textiles

Mehta, A. (2022). Gen Z fashion consumption: Influence of social media. https://www.researchgate.net/publication/366499971_Gen_Z_fashion_consumption_Influence_of_social_media

Nizzoli, G. (2022, April 6). How many times do we wear our clothes? (Not enough!). Project  

Cece. https://www.projectcece.com/blog/506/how-many-times-do-we-wear-our-clothes/ 

Prashar, A., & Kaushal, L. A. (2025). Nudging sustainable fashion choices: An experimental

investigation on generation Z fashion consumers. Acta Psychologica, 253. https://doi.org/10.1016/j.actpsy.2025.104727

Schwartz, B. (2015). The Paradox of Choice. In Positive Psychology in Practice Part II:

Values and Choices in Pursuit of the Good Life (pp. 121–138).

5/5 (1)

The use of AI is growing in many industries, particularly many creative industries, such as music, visual art, and writing. This is no surprise, since creatives have always been early adaptors of technological innovations to enhance their work process and artistic output (Caramiaux et al., 2019). In music, for instance, the NSynth tool, which has been trained offline on musical datasets via an underlying sound model, has been used in the mainstream music industry to generate new types of musical sounds. For visual art there are quite a few different GenAI platforms that are able to generate images, videos or other art pieces based on a description or other input. Think of Deep Dream and Artlist. Platforms like Squibler are AI story writers that can be used to write full-length books, screenplays, scripts, etc.

These uses of AI in creative industries raise many questions, especially about authenticity, ownership and the future of these industries. Critics of AI generated art argue that it lacks authenticity (Donelli, 2024). Art is supposed to be rooted in intent, emotion, and human skills. Art that is generated by AI may not capture the full depth of human creativity. Regarding ownership, it’s important to mention that no one can own the copyright to AI generated works (HLR, 2025). Therefore, it remains in the public domain (Copyright Alliance, 2023). There have been various waves of layoffs across creative industries because of the use of AI (Zhao, 2024). This may seem like a bleak outlook regarding the future of humans in creative industries, but we must remember that art is subjective and based on human tastes. Meaning that art will always depend on human experiences and emotions to be able to connect with other humans. No matter how evolved AI is, it does not understand humans like other humans do. Considering all of this, we would not have to worry about AI completely replacing humans in creative industries. However, considering the current uses of AI in these industries, we do have to be worried about a shift from humans actually making art to people simply making a prompt and showcasing output from AI based on this prompt as their own art.

References

Caramiaux, B., Lotte, F., Geurts, J., Amato, G., & Behrmann, M. (2019). AI in the media and creative industries (hal-02125504). New European Media. Retrieved September 17, 2025, from https://openresearch.amsterdam/nl/page/109044/ai-in-the-media-and-creative-industries

Copyright Alliance. (2023, August 29). Who owns the copyright to AI-Generated Works? | Copyright Alliance. https://copyrightalliance.org/faqs/artificial-intelligence-copyright-ownership/#:~:text=Works%20Solely%20Generated%20by%20AI,is%20in%20the%20public%20domain.

Donelli, F. (2024, September 4). Generative AI and the creative industry: Finding balance between apologists and critics. Medium. Retrieved September 18, 2025, from https://medium.com/@fdonelli/generative-ai-and-the-creative-industry-finding-balance-between-apologists-and-critics-686f449862fc

HLR. (2025, April 10). Artificial intelligence and the creative double bind. Harvard Law Review. Retrieved September 18, 2025, from https://harvardlawreview.org/print/vol-138/artificial-intelligence-and-the-creative-double-bind/

Zhao, B. (2024, March 28). Replacement of human artists by AI systems in creative industries. UN Trade and Development (UNCTAD). https://unctad.org/news/replacement-human-artists-ai-systems-creative-industries