Manavika Mirania

Artificial Intelligence (AI) is emerging as a transformative force in the fashion industry, with Generative AI (GenAI) capable of synthesising sketches, garment patterns, and textures to generate realistic design options. These systems can autonomously produce, evaluate, and refine outputs based on diverse inputs. While much of GenAI’s promise lies in creative and product development, its adoption in fashion design remains tentative and uneven across the industry.

In India, design-led brands operate through customised business models, artisan-led production, and labour-intensive workflows. These dynamics present both challenges and opportunities: AI has the potential to streamline processes and enhance creative exploration, yet adoption is constrained by culturally embedded, narrative-driven practices. This study addresses the gap by examining how AI can support creativity and efficiency while respecting the cultural and artisanal foundations of Indian designer fashion. Its purpose is to explore how AI can be integrated in ways that balance human ingenuity with technological innovation.

The research is anchored in an interpretivist paradigm and adopts a qualitative, exploratory approach. Semi-structured interviews were conducted with designers and founders across luxury, premium, and accessible designer brands. An inductive analysis of these accounts provided insight into how brands are currently using, perceiving, and approaching AI. Thematic analysis was employed to examine narratives in depth and to capture perspectives on AI integration within creative workflows.

Overall findings indicate that technology adoption in this sector is cautious and partial, with AI use remaining peripheral rather than strategic. Both industry evidence and academic studies suggest that while AI holds promise for ideation, visualisation, and documentation, it must operate in a supporting role that safeguards cultural literacy, artisanal knowledge, and human authorship. Barriers extend beyond technical limitations to include human readiness, gaps in AI literacy and training, ethical considerations, and uncertainties around intellectual property.

The study concludes that successful integration of AI in Indian design-led fashion requires more than technological innovation. It emphasises the need to understand appropriate use cases (How to use it and where); to cultivate leadership awareness and alignment at the founder and director level; and to embed structured training that enhances AI literacy across design teams. The findings also underline the importance of establishing governance frameworks that clarify authorship, data ethics, and intellectual property, alongside the development of context-sensitive tools capable of representing Indian craft traditions and material complexity.

Overall, the study positions AI not as a replacement for human creativity but as a collaborator that can expand possibilities and enhance efficiency when deployed with caution, cultural sensitivity, and strategic foresight. Its future role in Indian fashion will depend on the balance achieved between technological opportunity and human creativity, ensuring that innovation strengthens rather than dilutes the cultural and artisanal depth that defines this sector.