Generative AI in Fashion Design: Creativity Meets Computational Intelligence

Authors- Sadiq H

Abstract--The fusion of artificial intelligence with creative industries has opened new dimensions for innovation, especially in fashion design. Generative Artificial Intelligence (AI)—powered by models such as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and diffusion models—enables machines to learn aesthetic patterns and autonomously generate original clothing designs, textiles, and style variations. This paper explores the foundations of generative AI in the context of fashion, focusing on how computational intelligence can augment human creativity. It discusses practical use cases such as automated design generation, virtual try-ons, trend forecasting, and customization. Real-world case studies from global fashion houses, startups, and online retailers demonstrate how generative AI is transforming the design process, reducing production cycles, and enabling more sustainable practices. Ethical and regulatory considerations related to originality, intellectual property, cultural appropriation, and labor displacement are critically examined. The paper also highlights challenges such as data bias, model interpretability, and integration with existing workflows. Looking ahead, future prospects including AI-human co-creation platforms, sustainable design automation, and emotionally intelligent fashion systems are explored. Generative AI represents a paradigm shift in fashion design, offering novel opportunities while redefining the relationship between technology and artistic expression.

DOI: /10.61463/ijset.vol.13.issue2.379