In the evolving landscape of cultural heritage preservation, emerging technologies such as Extended Reality (XR) and Artificial Intelligence (AI) are reshaping how archival and heritage content are preserved, documented, interpreted, and promoted. These technologies enable interactive and immersive experiences that foster deeper engagement and cultural appreciation. Traditional clothing worn during folk dancing is a key element of both tangible and intangible cultural heritage, as it is associated with movement, shapes, materials, craftsmanship, and historical context. This study explores how emerging technologies can support the preservation and promotion of traditional costumes by examining the current state of the art in digitization and interactive presentation, with particular focus on movement and interactivity. It also reviews case studies involving AI applications in the field of traditional heritage clothing as well as in the contemporary fashion retail sector. The aim is to identify gaps in the existing XR pipelines and investigate areas where AI can contribute—drawing also on successful paradigms from the retail industry, to inform possible applications in the heritage domain. Through an analysis of representative studies and projects, the review highlights growing interest in immersive experiences and 3D garment reconstruction. However, significant gaps remain in the dynamic, motion-aware, and interactive representation of costumes, especially in the context of dance. The study examines how AI can assist various stages of the digital heritage costume pipeline, including metadata enrichment, generative reconstruction, motion simulation, and user experience evaluation. It also identifies domains where AI technologies are more mature and those where development is still emerging. Finally, the study outlines future research directions, particularly in AI-assisted animation, virtual try-on systems, and gamified cultural applications, advocating for a shift from passive digitization to context-aware, interactive, and embodied approaches that better reflect the complexity of traditional garments.