Textile and Apparel Industries

Improving Sustainability in Fashion Design Through Generative AI: Tools and Applications

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Abstract

Design for a sustainable future is a key goal for design communities, yet the complexity of generating sustainable designs creates challenges from concept exploration to final execution. While Generative AI can enhance creativity and optimize fashion processes, research examining its sustainability potential remains limited. This systematic literature review following PRISMA guidelines analyzed 30 peer-reviewed articles and industry reports (2022-2025) to identify how Generative AI tools improve sustainability in fashion design. Findings reveal three key applications: AI-powered trend forecasting and demand prediction reduce overproduction and optimize inventory management; image generation and design exploration tools minimize physical sampling and material waste during ideation; and AI-driven prototyping platforms reduce physical prototyping needs by up to 70%, decreasing resource consumption and transportation impacts. Results demonstrate Generative AI's potential to enhance sustainability across the fashion design workflow while maintaining creativity and design quality.

Keywords: Generative AI, Sustainable fashion, Fashion design tool

How to Cite:

Barsha, U. H., Ahmed, F., Wu, J. & Khan, B., (2025) “Improving Sustainability in Fashion Design Through Generative AI: Tools and Applications”, International Textile and Apparel Association Annual Conference Proceedings 82(1). doi: https://doi.org/10.31274/itaa.21921