Generative AI for Concept Ideation and Sketching
AI-generated concept design from G-Star RAW’s experimental AI collection, blending denim with whimsical 3D shapes. Such text-to-image tools allow fashion designers to rapidly visualise avant-garde ideas during ideation.
Generative AI has emerged as a powerful aid in the early concept development stage of fashion design, enabling rapid sketch generation, moodboard creation, and visual experimentation. Text-to-image models like OpenAI’s DALL·E, Midjourney, and Stable Diffusion can translate text prompts into fashion drawings or concept art within seconds. This allows designers to prototype sketches and silhouettes without laborious hand-drawing, especially when exploring novel themes. For example, a designer might prompt an AI for “futuristic evening gown with pleated wings in the style of Issey Miyake”, and receive a set of imaginative visuals to kickstart their creative process. Researchers have found that these tools provide “diverse and rapid visual stimuli”, significantly enhancing early-stage ideation by visualizing ideas that designers only vaguely envisioned. Even with minimal input, AI can generate a range of garment images with varied patterns, textures, and shapes, unshackled by the constraints of physical materials. Designers can then adapt or iterate on these AI-generated ideas, saving time while broadening their creative exploration.
https://www.globaltextiletimes.com/featured/is-generative-ai-really-disrupting-the-fashion-industry
https://aodr.org/xml/41431/41431.pdf
Generative AI is also being applied to automate moodboard building and concept boards. Specialized AI tools can ingest a theme or a set of inspiration images and output a curated collage of visuals aligning with the desired mood or color palette. An academic study from the NORDES 2023 conference demonstrated that a GAN-based system (using MidJourney) could produce a complete digital moodboard from a text prompt “in seconds and without retouch”, effectively visualizing a theme with multiple stylistic interpretations. The strength of such AI-generated moodboards lies in their ability to provoke imagination by combining styles and content in unexpected ways. For instance, an AI might blend Baroque-era opulence with cyberpunk elements on a concept board, inspiring designers to explore fusions they might not have considered. In practice, designers are beginning to use these prompt-to-moodboard and prompt-to-sketch tools to flesh out initial ideas. The Adobe “Project Concept” and other prototypes similarly show how generative AI can populate concept boards, suggesting silhouettes, fabric textures, and even color schemes based on a textual concept description (Yang et al., 2022). This augments traditional trend research and sketching by providing a rich visual starting point.
Beyond text input, generative AI supports variation generation from a base idea. Designers can feed a rough hand sketch or reference image into certain AI systems (often via image-to-image generation or diffusion models) to yield new interpretations. In one study, fashion designers used AI to enhance their own sketches: a rough hand-drawn coat was input and the AI produced more detailed renderings with different embellishments and fabric treatments. This process, termed “hand-drawn sketch enhancement,” is especially helpful for designers with weaker illustration skills, as the AI can fill in realism and details (Fashion Innovation Alliance, 2022). Similarly, designers used AI-driven style transfer to blend aesthetics – for example, applying the color palette of a sunset photo onto a dress sketch, or merging traditional cultural patterns with contemporary silhouettes. Early creative experiments by designer-researchers like Irina Raicu involved using neural style transfer to “combine features from two images”, breathing new life into her fashion illustrations by merging her drawings with textures from art or nature. This kind of style blending is now more accessible with diffusion-based tools, where a prompt can specify multiple influences (e.g. “a kimono meets streetwear, in pastel baroque style”) and yield a hybrid design. Generative AI algorithms, whether through explicit style transfer or through multimodal prompts, thus act as a creative spark – offering moodboard concepts, sketch variants, silhouettes and color ideas that designers can further refine.
https://aodr.org/xml/41431/41431.pdf
https://medium.com/tech-art-talks/the-waltz-of-ai-and-fashion
Examples of AI-human co-creation: AI produces initial options, designer curates or tweaks
AI-Human Co-Creation: Case Studies from Designers and Brands
Numerous case studies in the US and Europe illustrate how fashion designers are co-creating with AI, using generated outputs as a starting point and then applying human expertise to refine or realize those ideas. Rather than replacing designers, AI often serves as a collaborative partner that contributes novel options which the designer curates and develops. A 2024 study observed that designers view AI tools as “starting points for creativity, complemented by human expertise for practical implementation”. The following examples highlight this interplay in real-world design workflows:
1. G-Star RAW (Netherlands) – The Dutch denim brand pioneered an AI-human design collaboration for a capsule concept collection. The G-Star design team worked with Midjourney to generate 12 unique denim couture concepts via text prompts. These AI outputs included fantastical forms – e.g. a bulbous, futuristic denim ensemble with exaggerated silhouettes (see above image). Rather than simply treating them as art, the team selected one AI-generated concept and translated it into a physical garment by hand in their atelier. The result was an “AI Denim Cape”, an intricately folded denim piece with 3D swirls and signature G-Star details, which the brand produced as a one-of-a-kind showpiece
. This project was explicitly framed as a “unique collaboration between man and machine,” with G-Star’s human artisans bringing the AI’s vision to life. G-Star’s CMO, Gwenda van Vliet, explained that “while anyone could make a design using AI, at G-Star… we have the craftsmanship to make those designs into real garments. We should see AI as enhancing the creative process, rather than taking it over.”. In short, the AI proposed adventurous designs, and human designers exercised taste and technical skill to realize one, showcasing co-creation in action.
2. Collina Strada (USA) – New York-based label Collina Strada, led by designer Hillary Taymour, openly integrated AI into its Spring 2024 collection’s development. Taymour used generative AI (specifically Mid Journey) to create initial visuals for runway sculptures, clothing patterns, and prints. These AI-generated graphics and forms – which ranged from surreal animal prints to sculptural silhouettes – were not directly 3D-printed onto fabric, but they sparked ideas that her team then adapted into tangible designs. By Fall 2024, other American designers followed suit: couture designer Bach Mai and the label Monse both reported using AI to develop print concepts for their collections. In these cases, the designers treated the AI like a digital print designer – generating a flurry of pattern ideas, selecting the most promising ones, and tweaking colors or layout to fit their vision. The creative control remained with the human designers (who decided which AI outputs made sense for their brand aesthetic), illustrating a curation approach to AI co-creation.
3. Norma Kamali and Maison Meta (USA) – An especially illuminating case of human-AI co-creation is veteran designer Norma Kamali’s collaboration with AI agency Maison Meta to preserve and extend her creative legacy. At 78, Kamali worked with technologists to train a custom generative model on her brand’s 40+ year archive. By feeding thousands of her past designs and references into the AI, they created a tool capable of producing Kamali-esque designs from text descriptions. Kamali’s intent is for this AI to become a support tool for future designers at her brand – essentially an AI “assistant” that can suggest new garment ideas in her signature style even after she retires. Importantly, she views this not as an autonomous designer, but as a way to augment human designers: “The intent isn’t to have the machine replace human designers. [She] thinks AI has its limits, and it will require people with original ideas to make the best use of it.”. In practice, her team can input a concept (say, “70s-style sleeping-bag coat with modern twist”) and get AI-proposed sketches that they can refine and prototype. This case exemplifies co-creation where the AI is deeply tailored to a designer’s personal style DNA, and used as a creative brainstorming partner for humans – essentially bottling a designer’s sensibility and deploying it in tandem with new human ideas.
https://thearts.ai/can-ai-carry-on-designer-legacy
4. Luxury Brands Experimentation (Europe & USA) – Established fashion houses are also dabbling in co-creative processes with AI. Parisian couture house Dior in 2022 experimented with AI in a haute couture collaboration: Dior’s artisans used an AI tool to transform artist Faith Ringgold’s mosaic artworks into intricate embroidery layouts for a collection. Here the AI helped interpret artwork into fashion context, which human craftsmen then executed with needle and thread – a creative partnership bridging digital and hand-made art. Balmain (France) partnered with a startup called Ablo to use AI in designing a limited-edition sneaker, customizing the design via the tool before hand-finishing it. And Italian luxury houses like Moncler, Zegna, and Valentino have used AI-generated imagery in their creative campaigns, hinting that their design teams are at least co-piloting these new tools for visual development. In all these instances, AI provides suggestions, options, or translations of creative ideas, while human designers and makers provide judgment, refinement, and brand-specific know-how. The pattern that emerges is AI as an ideation partner: designers use it to widen the creative funnel (generate many ideas or variations), then rely on their trained eye and craft to pick and polish the final concepts.
https://digitaldefynd.com/IQ/christian-dior-using-ai-case-study/
https://www.worldfashionexchange.com/blog/artificial-intelligence-in-fashion/
These case studies underscore that AI-human co-creation is becoming a practical reality in fashion. Designers report that AI can inject fresh ideas that they might not have conceived solo – serving as a “co-designer” that brings in a touch of randomness or novelty. However, the human remains deeply involved as the editor, storyteller, and technical executor. As one study noted, “AI-generated designs are better suited for inspiration rather than final products, aiding in brand planning and image searches but requiring human intervention for execution and detailed design.” In essence, AI may sketch the first draft of a concept, but the designer provides the second draft and the final cut. This symbiosis is at the heart of current AI-fashion collaborations.