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As a strategic designer working at the intersection of technology and human-centered design, I experienced first-hand how generative AI is reshaping the traditional design process. During the Tech-Enabled Innovation Studio course at TU Delft, my team and I developed an AI-driven triage assistant for Dutch primary care. This course was a testing ground for exploring how tools such like Lovable, NotebookLM and Cursor could influence creativity and bridge technical and strategic thinking. By combining these tools, it became possible to create feedback loops across design stages, for instance, using ChatGPT to refine prompts for Lovable or iteratively improving Lovable’s chatbot functionality through Cursor’s code environment. Eventually, combining them as interconnected components within a data-driven workflow.

Hatchuel and Weil (2003) introduced C–K Theory as a new approach to innovative design. In this framework, the Concept Space (C-space) contains undeveloped ideas and hypotheses, while the Knowledge Space (K-space) holds established information and validated knowledge. I believe AI’s greatest strength lays in its ability to move quickly between Concept and Knowledge space. Within minutes, abstract prompts turned into tangible prototypes that could be tested and refined live with stakeholders like General Practitioners. Especially Loveable was super powerful in translating our ideas into artefacts. From a BIM perspective, this mirrors the dual process of data exploration and knowledge forming, central to information management. This allowed me to focus more on strategic decision-making and less on technical constraints, ultimately improving the collaborative and reflective nature of the design process.

Yet, the experimentation also revealed limitations. AI outputs often lacked depth or consistency after initial iterations, making it very difficult to maintain quality. Synthetic users, AI-generated representations of interview participants, were helpful for quick feedback but could never replace real human nuance. Moreover, the environmental footprint of continuous AI use added an ethical dimension to the conversation about responsible design and development.

This experience underscored that the future of digital innovation depends less on individual AI tools and more on the integration of intelligent systems within coherent information (work)flows. Generative AI can strengthen decision-making when combined with strong information architectures that ensure traceability, context, and human oversight. The role of the strategic designer or BIM professional, therefore, is to act as the leader and guider of these hybrid ecosystems, defining what AI should contribute to, aligning it with organisational goals and maintaining the balance between automation and human judgment.

Sources

Hatchuel, A., & Weil, B. (2003). A new approach of innovative design: An introduction to C-K theory. In Proceedings of the International Conference on Engineering Design (ICED 03), Stockholm, 19-21 August 2003. 

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Product design is traditionally a very time consuming and resource intensive practice. Hundreds of iterations are needed before a product is ready for large scale production. Starting with market and user research, prototyping, user testing and doing that over and over again to come to a well rounded, producible and desirable product. The costs for companies are high, but now: AI and VR are revolutionising design!

Prototyping Reinvented

To tackle these inefficiencies, industries are entering a new phase digitalisation. Where industry 3.0 was focused on basic automation IT via individual tasks, Industry 4.0 embeds intelligent automation, connectivity, collaboration and data-driven insights (Vaidya, Ambad, & Bhosle, 2018).

One clear example of this shift is in prototyping, where VR tools such as Gravity Sketch are transforming workflows. Within the realm of prototyping and iteration, Gravity Sketch stands out as an application that immerses designers in a digital studio. It fits the overall trend of more intelligent automation by combining digital simulations and collaboration. It allows for a new form of human-machine interaction that was not previously possible (Seman, Ismail, & Mohamed, 2022). For example if we look at automotive design projects can take weeks, with the usage of gravity sketch, it has seen time reductions of up to 60% (Immersive Tech Network, 2022).

Similarly, AI tools are reshaping the early stages of design, particularly the diverging ideation phase. Adobe’s Firefly allows designers to instantly generate multiple variations from a single prompt, providing a rapid way to explore form, material and style directions (Jiang, 2024).

AI and VR contribute to design workflows in different ways. Firefly’s acceleration of idea generation allows teams to explore a much wider solution space in less time, ensuring that promising directions are identified earlier in the process. In contrast to Firefly’s generative nature, VR tools like Gravity Sketch do not (yet) generate content on their own, but instead immerse designers in an interactive environment where they can model collaboratively.

While these tools could accelerate creativity, they also introduce new ethical concerns. Intellectual property is one of the most pressing: when AI systems generate concepts trained on vast datasets, who owns the output, the designer, the company, or the creators of the original training data? Questions of authorship, originality, and copyright are becoming increasingly complex.

Evolving role of designers

These new workflows and challenges don’t just affect companies as a whole, they reshape the role of the designer. Perhaps the future of product design is less about drawing the first line and more about deciding which lines are worth keeping. In that sense, designers may shift from designer to sense-maker: deciding the direction, embedding ethical considerations and ensuring that technology serves a positive impact on people and planet.

How do you see VR and AI tools like Gravity Sketch or Firefly changing workflows in your own industry or domain, if at all?

Sources

Seman, N. A. A., Ismail, N., & Mohamed, M. A. (2022). Design creativity in Industry 4.0: Gravity Sketch as a virtual reality tool for creative design. Journal of Engineering, Design and Technology, 22(5), 1413–1429. https://doi.org/10.1108/JEDT-08-2021-0488

Vaidya, S., Ambad, P., & Bhosle, S. (2018). Industry 4.0 – A glimpse. Procedia Manufacturing, 20, 233–238. https://doi.org/10.1016/j.promfg.2018.02.034

Immersive Tech Network. (2022). Gravity Sketch: Case study. Innovate UK. https://iuk.immersivetechnetwork.org/case-study/gravity-sketch/

Jiang, J. (2024). When generative artificial intelligence meets multimodal composition: Rethinking the composition process through an AI-assisted design project. Computers and Composition, 74, 102883. https://doi.org/10.1016/j.compcom.2024.102883