Abstract
Generative AI is increasingly shaping the workflows of digital cultural heritage design practice, introducing new approaches to creative production, interpretation, and collaboration. Existing research has examined how generative AI influences general design workflows and supports creative practices in different domains. However, limited attention has been given to how these technologies participate in the design workflows of digital cultural heritage. Compared with other design contexts, digital cultural heritage design requires balancing creative exploration with the accurate transmission of heritage knowledge, which makes its workflows more complex. To address this gap, this study conducts a systematic literature review to examine how generative AI participates in different stages of digital cultural heritage design practice. It investigates the roles, methods, and impacts of generative AI in these workflows and aims to provide a structured understanding of this evolving field for future research and practice.
Keywords
digital cultural heritage, design workflow, generative AI
DOI
https://doi.org/10.21606/drs.2026.791
Citation
Zhang, Y., Yang, T., Li, M., and Wang, Y. (2026) Generative AI in Digital Cultural Heritage Design Workflows: A Systematic Literature Review, 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.2026.791
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Included in
Generative AI in Digital Cultural Heritage Design Workflows: A Systematic Literature Review
Generative AI is increasingly shaping the workflows of digital cultural heritage design practice, introducing new approaches to creative production, interpretation, and collaboration. Existing research has examined how generative AI influences general design workflows and supports creative practices in different domains. However, limited attention has been given to how these technologies participate in the design workflows of digital cultural heritage. Compared with other design contexts, digital cultural heritage design requires balancing creative exploration with the accurate transmission of heritage knowledge, which makes its workflows more complex. To address this gap, this study conducts a systematic literature review to examine how generative AI participates in different stages of digital cultural heritage design practice. It investigates the roles, methods, and impacts of generative AI in these workflows and aims to provide a structured understanding of this evolving field for future research and practice.