From couture to code: Reimagining fabric development through AI-enhanced material narratives

As artificial intelligence (AI) becomes more embedded in fashion design, questions arise about the values these systems encode. Current tools emphasize speed, novelty and surface aesthetics, often overlooking the cultural, emotional and material dimensions of sustainable practice. This article proposes Slow AI: a speculative, ethically grounded framework rooted in fabric memory, narrative depth and material literacy. Drawing on material culture theory and studio-based research, it critiques how generative AI simulates sustainability while neglecting provenance and care. Through case studies of Marine Serre, BODE and FAÇON JACMIN, the article shows how designers already model the relational intelligence AI might one day support. A speculative toolkit outlines functions such as archive mapping, emotionally annotated datasets and story-aligned prompts. Rather than accelerating production, Slow AI reframes design as a process of co-authorship, rooted in repair, friction and the ethics of making.