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<p>This study investigates the strategic application of generative artificial intelligence (GenAI) tools in fashion collection development, examining how AI can enhance creative processes while maintaining design authenticity. The research addresses the gap between technical AI capabilities and their practical implementation in fashion design methodologies. Using Treptow’s (Inventando moda: planejamento de colecao, 5th edn. D. Treptow, São Paulo, <CitationRef CitationID="CR25">2013</CitationRef>) four-stage fashion collection development framework (Planning, Design, Development, and Promotion/Commercialization), this experimental study employed structured prompt engineering with Claude 3.5 Sonnet, ChatGPT-4o mini, and DALL·E to simulate luxury beachwear collection development. Multiple AI illustrative personas were created to represent different professional roles, generating outputs for trend research, design alternatives, visual development, prototype approval, and marketing strategies. A qualitative analysis examined the effectiveness and limitations of AI integration across each development phase. Results demonstrate that well-crafted prompts can effectively guide AI tools to produce relevant design concepts, trend analyses, and marketing strategies that align with traditional fashion development processes. However, significant limitations emerged in visual consistency and collection cohesion, particularly in comprehensive design visualization. The study reveals that AI functions most effectively as a creative amplifier rather than a replacement, requiring substantial human oversight for maintaining design integrity and brand authenticity. The findings have implications for fashion education, suggesting the need for AI literacy integration in design curricula. Fashion professionals can leverage structured prompt engineering to accelerate ideation, trend research, and marketing development while maintaining creative control. This research contributes the first systematic framework for applying GenAI across the complete fashion collection development cycle, providing empirical evidence of AI’s capabilities and constraints in creative fashion processes.</p>

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Strategic use of generative AI in fashion collections: from creation to promotion

  • 期刊论文

  • 发表日期：

    2026年1月16日

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  • Thaissa Schneider,
  • Cristiani Maximiliano,
  • Laura Pedri Pereira,
  • Doris Treptow,
  • Samuel Levi Araújo Alves

摘要

This study investigates the strategic application of generative artificial intelligence (GenAI) tools in fashion collection development, examining how AI can enhance creative processes while maintaining design authenticity. The research addresses the gap between technical AI capabilities and their practical implementation in fashion design methodologies. Using Treptow’s (Inventando moda: planejamento de colecao, 5th edn. D. Treptow, São Paulo, 2013) four-stage fashion collection development framework (Planning, Design, Development, and Promotion/Commercialization), this experimental study employed structured prompt engineering with Claude 3.5 Sonnet, ChatGPT-4o mini, and DALL·E to simulate luxury beachwear collection development. Multiple AI illustrative personas were created to represent different professional roles, generating outputs for trend research, design alternatives, visual development, prototype approval, and marketing strategies. A qualitative analysis examined the effectiveness and limitations of AI integration across each development phase. Results demonstrate that well-crafted prompts can effectively guide AI tools to produce relevant design concepts, trend analyses, and marketing strategies that align with traditional fashion development processes. However, significant limitations emerged in visual consistency and collection cohesion, particularly in comprehensive design visualization. The study reveals that AI functions most effectively as a creative amplifier rather than a replacement, requiring substantial human oversight for maintaining design integrity and brand authenticity. The findings have implications for fashion education, suggesting the need for AI literacy integration in design curricula. Fashion professionals can leverage structured prompt engineering to accelerate ideation, trend research, and marketing development while maintaining creative control. This research contributes the first systematic framework for applying GenAI across the complete fashion collection development cycle, providing empirical evidence of AI’s capabilities and constraints in creative fashion processes.