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Design & R&D · Concept
Generative AI / Visual & Shape Generation
Fast concept visualisation in early product ideation
Live Core high effect
Core capability
The technology speeds up early concept exploration by turning rough ideas into visual 3D form quickly, which is useful in the ideation stage even when the output is not yet engineering-grade CAD.
How it works
The user provides an idea in text or a visual reference, and the model gradually refines that input into a rough 3D concept that can be reviewed early in the design process.
Application here
From a text description or sketch, the system generates concept visuals and 3D shapes in minutes for design reviews.
Business impact
This lets teams explore many more concept variants much earlier, accelerating alignment before detailed design begins.
Limitations
The output is a visual placeholder, not manufacturable geometry. Strong-looking visuals can also give a false sense of concept maturity.
In production
This is already useful in concept work, where teams need to explore ideas quickly and communicate shape direction before investing in detailed engineering.
Research
The frontier is moving from fast visual concepts toward generated shapes that also respect practical engineering constraints such as manufacturability, structural logic, and assembly fit.
Examples
McKinsey Report: Generative AI in Product Design
Description: Automotive OEM designers used gen AI to generate 25 variations of next-gen car dashboard concepts, including touch screens and charging surfaces, in two hours for early stakeholder reviews before refinement.



NexGen Cloud Case Study: GM Seatbelt Bracket Redesign
Description: General Motors partnered on generative AI to redesign a seatbelt bracket, producing a 40% lighter, 20% stronger single-part design from constraints, cutting costs and boosting EV efficiency in production.



Coolhunting Article: BMW Designworks AI Ideation
Description: BMW Designworks uses proprietary AI to blend past products with external objects via dials, generating car concepts instantly for early ideation, animating static images to 3D for rapid iteration cycles.
https://www.mckinsey.com/capabilities/tech-and-ai/our-insights/generative-ai-fuels-creative-physical-product-design-but-is-no-mahttps://www.nexgencloud.com/blog/case-studies/top-use-cases-of-generative-ai-in-the-automotive-industryhttps://coolhunting.com/design/bmws-designworks-studio-uses-ai-to-design-for-the-future/
Sources
Midjourney — ; OpenAI DALL-E —
https://www.midjourney.com/https://openai.com/dall-e/