Abstract
This paper is based on interviews with 20 expert industrial designers with 8-40+ years of experience about how they are adopting generative AI into their workflows. Using thematic analysis, the study reveals how top-down pressure for speed and efficiency drives rapid, bottom-up adoption of generative AI tools. The core finding is that in this scramble for adoption, designers and design businesses risk cognitive offloading and significant loss of control over micro-decisions in key parts of the design process. By critically examining the potential loss of control and reflection, the inquiry explores how the value of industrial design work extends far beyond generating contextless output and what consequences this has for generative AI implementation. The investigation concludes with an actionable roadmap for decision-makers in industrial design businesses, considering when to adopt generative AI.
Keywords
Generative AI; Industrial design; Reflective practice; Design business
DOI
https://doi.org/10.21606/drs.2026.2166
Citation
Abrahamsen, T., and Sjödell, C. (2026) A survey of generative AI adoption amongst industrial design experts, in Simeone, L., Gray, C. M., Verhoeven, A., de Götzen, A., Bakırlıoğlu, Y., Zohar, H., Stead, M., and Buwert, P. (eds.), DRS2026: Edinburgh, 8–12 June, Edinburgh, United Kingdom. https://doi.org/10.21606/drs.2026.2166
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Included in
A survey of generative AI adoption amongst industrial design experts
This paper is based on interviews with 20 expert industrial designers with 8-40+ years of experience about how they are adopting generative AI into their workflows. Using thematic analysis, the study reveals how top-down pressure for speed and efficiency drives rapid, bottom-up adoption of generative AI tools. The core finding is that in this scramble for adoption, designers and design businesses risk cognitive offloading and significant loss of control over micro-decisions in key parts of the design process. By critically examining the potential loss of control and reflection, the inquiry explores how the value of industrial design work extends far beyond generating contextless output and what consequences this has for generative AI implementation. The investigation concludes with an actionable roadmap for decision-makers in industrial design businesses, considering when to adopt generative AI.