Generative Artificial Intelligence (AI) is rapidly transforming the design industry, particularly in the fashion industry, by offering new ways to create, innovate, and scale ideas. This research evaluates the creative and practical benefits of Generative AI tools, examines the extent of access these systems hold to existing design data, and addresses the concerns around plagiarism and intellectual property protection within the AI design ecosystem.

The research methodology combines a multi-layered approach. Firstly, existing case studies documenting AI’s role in design processes are analysed. Secondly, surveys were conducted with industry professionals to gauge AI’s utility and risks. Lastly, direct observation of AI outputs in response to targeted prompts across platforms such as ChatGPT, Gemini, Perplexity, and Midjourney. This method ensures that both theoretical and applied perspectives are depicted.

The study demonstrates that while generative AI facilitates rapid prototyping, customization, and creative exploration, it also introduces risks of homogenization and diminished originality. The findings suggest that AI functions most effectively as a supplementary design tool rather than a full creative substitute. Empirical observations confirmed that AI systems were unable to surpass paywalls on design platforms; however, once designs entered the public domain, replication became easier. Survey data further revealed concern among respondents regarding plagiarism. Analysis of different case studies indicated that methods such as watermarking and the mandatory disclosure of AI involvement may mitigate disputes. 

Findings are limited by the rapidly evolving nature of AI tools, small sample sizes in surveys, and the inconsistency of measuring plagiarism incidents directly linked to AI. Generative AI is a powerful ally in design but cannot yet replace human creativity. Clearer rules, stronger protections, and ethical practices are needed to ensure its responsible use.