AI-Aided Gown Making: Humanizing Technology in Fashion Design and Production

The growing integration of Artificial Intelligence (AI) into fashion design and production presents opportunities for greater efficiency, personalization, and innovation; however, limited research has examined how AI can be applied to formal gown making while preserving human creativity, cultural sensitivity, and artisanal craftsmanship, particularly in local fashion contexts. This study aimed to examine the integration of AI-assisted technologies in the design and production of formal gowns and assess their potential to support human-centered fashion practices. A quantitative research approach was employed, with data collected from fashion designers and related stakeholders in Palompon, Leyte, and analyzed using appropriate statistical techniques. Findings indicated that AI-assisted technologies can support design ideation, fabric simulation, fit prediction, personalization, material efficiency, and production processes. Participants also identified concerns related to cultural sensitivity, design authenticity, creative ownership, and the possible reduction of artisanal value. The results suggest that the perceived usefulness and ease of using AI-assisted technologies influence stakeholders’ willingness to incorporate these tools into gown-making practices. The study concludes that AI is most valuable when used as a co-creative tool that complements rather than replaces human expertise. The study contributes a context-specific perspective on human–AI collaboration in fashion and provides practical insights for the responsible adoption of AI in gown making and fashion education, with potential benefits for creative innovation, sustainable production, and the preservation of human-centered craftsmanship.

Artificial Intelligence, Gown Making, Human–AI Collaboration, Fashion Technology, Sustainable Fashion

1. Bye, E. (2010). A direction for clothing and textile design research. Clothing and Textiles Research Journal, 28(3), 205–217. https://doi.org/10.1177/0887302X10371505 [Google Scholar] [Crossref]

2. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008 [Google Scholar] [Crossref]

3. Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep learning. MIT Press. [Google Scholar] [Crossref]

4. International Organization for Standardization. (2011). ISO/IEC 25010:2011: Systems and software engineering—Systems and software quality requirements and evaluation (SQuaRE)—System and software quality models. International Organization for Standardization. [Google Scholar] [Crossref]

5. Nielsen, J. (1994). Usability engineering. Morgan Kaufmann. [Google Scholar] [Crossref]

6. Norman, D. A. (2013). The design of everyday things: Revised and expanded edition. Basic Books. [Google Scholar] [Crossref]

7. Park, H., & Kim, Y. (2020). Artificial intelligence in fashion industry: A review of design and innovation applications. International Journal of Fashion Design, Technology and Education, 13(3), 350–360. [Google Scholar] [Crossref]

8. Russell, S., & Norvig, P. (2021). Artificial intelligence: A modern approach (4th ed.). Pearson. [Google Scholar] [Crossref]

9. Schenk, P., & Holman, R. (2000). Exploring the concept of fashion design creativity. Fashion Theory, 4(3), 289–308. https://doi.org/10.2752/136270400778995471 [Google Scholar] [Crossref]

10. Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540 [Google Scholar] [Crossref]

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