PUBLICATIONS

Rizzi, G., & Bertola, P. (2025). Exploring the generative AI potential in the fashion design process: an experimental experience on the collaboration between fashion design practitioners and generative AI tools. European Journal of Cultural Management and Policy, 15, 13875.

https://doi.org/10.3389/ejcmp.2025.13875

ABSTRACT

In recent years, the rise of Generative Artificial Intelligence (Gen AI) has led to the emergence of numerous tools for creating visual and textual content. This technological advancement, supported by increasingly robust data management systems and targeted research efforts in this direction, has driven the continuous refinement of Machine Learning and Deep Learning models. As a result, Gen AI tools have demonstrated ever-increasing performance, leading to their rapid adoption in various sectors, including the Cultural and Creative Industries (CCI). Here, they are being integrated into value-creation pipelines, potentially impacting both production processes and career prospects for creative professionals. As a consequence, critical questions have emerged about the widespread use of Gen AI, related to the nature of their generative capabilities, often encapsulated under the umbrella term of “computational creativity,” which has begun to challenge the traditional conception of creativity as an intrinsic and exclusive capacity of human beings, with implications across all fields in which human creativity is central, such as the design disciplines. In light of the current scenario, the presented research aims to discuss the application of Gen AI tools for image, text, and video generation in fashion design. The analysis draws on the results of a didactic laboratory entitled Artificial A(i)rchive, which involved design practitioners from the Master’s degree course in Design for the Fashion System at Politecnico di Milano. Within this workshop, the adoption of Gen AI was investigated, examining how AI was integrated at various stages of the design process and highlighting both the potential and shortcomings of applying Gen AI to support the activities of fashion designers. The article thus aims to contribute to the discussion and identification of collaborative models between fashion designers and AI, while situating the findings within a broader reflection on emerging creative practices and their potential implications.

Rizzi, G., & Casciani, D. (2025). Scouting emerging AI applications in fashion heritage and archival practices. European Journal of Cultural Management and Policy, 15, 14963.

https://doi.org/10.3389/ejcmp.2025.14963

ABSTRACT

Artificial intelligence (AI) increasingly influences the Cultural and Creative Industries (CCIs), offering new ways to support and enhance the sector. In the field of cultural heritage, AI has proven valuable across various disciplines, assisting in restoration, reconstruction, and the enrichment of historical knowledge. This paradigm opens new perspectives for fashion heritage, where AI technologies contribute to the preservation, reinterpretation, and dissemination of digitised archival materials, including garments, textiles, sketches, and photographs. This article investigates how AI is being integrated into fashion heritage practices by combining academic literature with practice-based evidence. Through an integrative review, it identifies three main trajectories of application: Conservation, Reinterpretation, and Exploration. These clusters highlight how AI is reshaping archival workflows, expanding access, and supporting new creative and curatorial approaches. The intersections between the trajectories give rise to the Creative Recovery, Heritage Imaginaries, and Augmented Access, which enable hybrid practices in current AI applications. The study concludes with a critical reflection on the main ethical concerns, including legal issues, economic implications, and concerns about data representation. These reflections are accompanied by a broader reconsideration of how memory is constructed and mediated in the contemporary context, increasingly shaped by human–AI collaboration.

Rizzi, G., & Vandi, A. (2025). Towards Synthetic Imaginaries: Augmenting Fashion Product, Communication, and Retail Design with GAI. In International Conference on Fashion Communication: between tradition and future digital developments (pp. 211-224). Cham: Springer Nature Switzerland.

https://doi.org/10.1007/978-3-031-99481-4_16

ABSTRACT

Recent Generative AI advancements, resulting in sophisticated image-generation tools, are revolutionising the Cultural and Creative Industries, impacting the entire value chain. In fashion design, these tools have become integral to the industry pipeline, supporting designers at various stages of creative processes. In particular, by leveraging vast datasets to generate synthetic images, AI has the potential to transform fashion archives into dynamic resources, enabling brands to explore and reimagine their visual heritage. Within this transformative context, the paper explores how designer-AI co-created outputs can be applied across three distinct areas of fashion design: Product development, Communication, and Retail. Through case study analysis, three trajectories are delineated to enhance fashion visual language and renew creative processes. Ethical issues related to reconfiguring the fashion designer’s role will be addressed, contributing to the ongoing debate on the relationship between human and AI creativity.

Rizzi, G., & Casciani, D. (2023). AI into fashion processes: laying the groundwork. Fashion Highlight, (2), 12-20.

https://doi.org/10.36253/fh-2490

ABSTRACT

The article aims to provide a comprehensive understanding of Artificial Intelligence (AI) and its integration into fashion processes, focusing on the research, design, development, and manufacturing stages. First, it offers an overview of AI evolution, from its early developments to the contemporary advanced Machine and Deep learning models, attempting to tackle the challenge of ambiguous terminology and aiming to deal with the different interpretations of AI capabilities. Subsequently, a review of the perspectives on the integration of AI tools within fashion processes will be presented. This overview will underscore the growing need for industries to undergo a conscious technological transformation, adopting AI toward a more sustainable and responsible fashion evolution.

Rizzi, G., & Vandi, A. (2023). Artificial intelligence in fashion design education: redefining creative processes towards designer-ai co-creation. In ICERI2023 Proceedings (pp. 3905-3912). IATED.

https://doi:10.21125/iceri.2023.0977

ABSTRACT

The rapid spread of Artificial Intelligence is reshaping the Cultural and Creative Sectors, challenging professionals and educational institutions to rethink competencies, curricula, and creative processes. The Digital Education Action Plan 2021–2027 underlines the crucial role of education in promoting AI literacy and supporting new forms of learning and teaching, particularly within disciplines rooted in ideation, planning, and visual materialisation. In Fashion Design, generative AI tools are transforming how designers translate inspirations from mood and lifestyle boards into shape and material outputs such as silhouettes, fits, prints, and constructions. This accelerates ideation and allows designers to quickly visualise prototypes, while simultaneously raising critical questions about authorship, data privacy, copyright, and the conceptual overlap between human creativity and machine generation. This paper investigates the implications of integrating AI into Fashion Design practice and academic curricula. Specifically, it examines the state of the art of AI in Education and the potential implementation of current AI tools to include fashion knowledge within datasets, going beyond their current ability to generate purely descriptive synthetic images. It then codifies the designer's role in human-AI co-creation and defines the boundaries between human and computational creative effort, contributing to a broader re-evaluation of the concept of creativity in AI-mediated professional and educational contexts.

Schnapp, J., Vandi, A., & Rizzi, G. (2024). L’ARCHIVIO DAL VIVO: DAL PROGETTO ALL’ALGORITMO. In Gianfranco Ferré dentro l'obiettivo (pp. 143-171). Forte di Bard Editore.

ABSTRACT

Contemporary archives are undergoing a profound transformation, shifting from static repositories to dynamic platforms for knowledge dissemination and creative reinterpretation. This paper presents the research activities developed at the Gianfranco Ferré Research Center at Politecnico di Milano, focusing on the role of generative AI in reinterpreting fashion heritage through the project "Ferré's vocabulary: from design to algorithms." Using a striped silk duchesse jacket from the 1985 Ready-to-wear collection as its central thread, the project brings Ferré's design principles into dialogue with AI-mediated visual exploration. Through interaction with generative AI tools, archival materials, patterns, and photographs, fabric samples become a living dataset from which new reinterpretations are generated, creating a continuum between human creativity and machine generation. The paper reflects on the implications of this shift, questioning the boundaries of authorship and creativity, and proposing the archive as a dynamic resource for cultural transmission and innovation in fashion heritage contexts.

Rizzi, G., & Bertola, P. (2023). A Perspective of University and Fablab Networks to Integrate Sustainability into Fashion Design Curricula through Industry 4.0 Technologies. In EDULEARN23 Proceedings (pp. 6450-6459). IATED.

http://doi: 10.21125/edulearn.2023.1712

ABSTRACT

The current climate crisis and the European Green Deal are driving a profound transformation of social and economic systems, in which Industry 4.0 technologies emerge as key enablers of sustainability goals rooted in the Twin Transitions framework. This transformation inevitably impacts higher education, which is called to rethink its role in training new professionals capable of navigating the challenges of contemporary society through transversal and interconnected skills. Through a literature review, this paper investigates the evolutionary path of Fashion Design curricula and proposes a trajectory of innovation in academic didactics centred on a Universities–FabLabs Networking perspective. This model advocates for a shift from passive learning to a Learning-by-doing strategy, in which theoretical knowledge becomes concrete experimentation through digital prototyping, bio-materials research, and advanced production techniques available within local FabLab networks. The proposed framework aims to integrate sustainability principles into fashion education, fostering collaborative learning and breaking the boundaries of the academic sphere to extend knowledge to the broader local ecosystem.

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