TLDR: A recent study by Pusan National University highlights how generative AI, including models like ChatGPT and DALL-E 3, is set to revolutionize the fashion industry. The research demonstrates AI’s capacity to enhance design creativity, streamline development processes, and accurately predict fashion trends, offering significant advancements for both professionals and the general public.
Generative Artificial Intelligence (AI) is on the cusp of fundamentally reshaping the fashion and textile industry, according to groundbreaking research conducted by Pusan National University in South Korea. The study, led by Professor Yoon Kyung Lee and Master’s student Chaehi Ryu from the Department of Clothing and Textiles, explores the profound potential of AI models such as ChatGPT and DALL-E 3 to enhance design efficiency, foster creativity, and accurately forecast market trends.
The research, published in the ‘Clothing and Textiles Research Journal’ on June 22, 2025, underscores how advanced generative AI tools can produce novel text and imagery, thereby streamlining fashion design workflows. Professor Lee emphasized the critical need for a deep understanding of these AI models to effectively deploy them in fashion. “To use AI effectively in fashion, we must understand the characteristics of generative AI models and make informed judgements of where they can be applied,” Professor Lee stated. The study specifically investigated the role of effective prompt engineering in generating realistic fashion collection images through AI.
In their methodology, the researchers utilized ChatGPT-3.5 and ChatGPT-4 to analyze historical men’s fashion trends up to September 2021, subsequently predicting trends for the Fall/Winter 2024 season. DALL-E 3 was then employed to visually capture these seasonal trends and conceptualize entirely new fashion collections. The findings indicate that while AI can significantly accelerate the design process and expand creative possibilities, the success of AI-generated designs heavily relies on expertly crafted prompts from fashion professionals.
Professor Lee further noted the broader implications of their findings: “Our results show that expertly worded prompts are necessary for accurate fashion design implementation of generative AI, highlighting the important role of fashion experts. With further learning and improvements, generative AI models like DALL-E 3 will help fashion designers create entire fashion collections more efficiently, while supporting their creativity, and also help non-experts understand fashion trends.”
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Beyond accelerating concept creation and exploring countless design variations, the integration of generative AI is expected to contribute to more sustainable practices within the industry by reducing waste through better-targeted designs and improved market alignment. This technological leap promises to make fashion exploration, prediction, and styling more accessible and efficient for both seasoned designers and the general public, marking a significant step towards a more innovative and responsive fashion landscape.
