Generative AI in the Applied Arts: Workflow Transformations, Evolving Professional Roles, and Emerging Skill Sets

Generative Artificial Intelligence (Gen AI) is rapidly reshaping the landscape of creative practice in the applied arts. While these tools accelerate ideation and support iterative prototyping, they also challenge traditional notions of authorship, authenticity and professional identity. This qualitative study explores how applied arts professionals integrate Gen AI into their workflows, what challenges they face, and what new skills and literacies they see as essential. Through purposive sampling, ten professionals, including designers, art directors, and filmmakers from diverse cultural contexts, were interviewed using semi-structured interviews. Thematic analysis identified two central themes: AI-driven workflow transformations and shifts in professional identity. Participants described Gen AI as a co-creator that enhances early conceptual work but also raised concerns around creative homogenization and ethical use of training data. These findings reinforce broader discussions in the literature about the dual role of AI as both a catalyst for innovation and a force that challenges creative diversity and cultural representation. The study highlights the need for a balanced approach to AI literacy in creative fields, one that integrates technical fluency with critical and ethical awareness. These insights provide a foundation for more nuanced, culturally sensitive, and ethically grounded approaches to AI adoption in the applied arts.

Authors

Publication Details

Journal
Informatics in Education
Published
2025-12-19
DOI
https://doi.org/10.15388/infedu.2025.23
Primary Topic
Art, Technology, and Culture
Type
article
Field-Weighted Citation Impact
0.00

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article

Generative AI in the Applied Arts: Workflow Transformations, Evolving Professional Roles, and Emerging Skill Sets

Sonia Andreou, Aekaterini Mavri, Andri Ioannou, Omiros Panayides et al.
Informatics in Education
Art, Technology, and Culture
article

Generative AI in the Applied Arts: Workflow Transformations, Evolving Professional Roles, and Emerging Skill Sets

Sonia Andreou, Aekaterini Mavri, Andri Ioannou, Omiros Panayides, Wesley Reges Soares Pereira, Eva Korae
article en

Abstract

Generative Artificial Intelligence (Gen AI) is rapidly reshaping the landscape of creative practice in the applied arts. While these tools accelerate ideation and support iterative prototyping, they also challenge traditional notions of authorship, authenticity and professional identity. This qualitative study explores how applied arts professionals integrate Gen AI into their workflows, what challenges they face, and what new skills and literacies they see as essential. Through purposive sampling, ten professionals, including designers, art directors, and filmmakers from diverse cultural contexts, were interviewed using semi-structured interviews. Thematic analysis identified two central themes: AI-driven workflow transformations and shifts in professional identity. Participants described Gen AI as a co-creator that enhances early conceptual work but also raised concerns around creative homogenization and ethical use of training data. These findings reinforce broader discussions in the literature about the dual role of AI as both a catalyst for innovation and a force that challenges creative diversity and cultural representation. The study highlights the need for a balanced approach to AI literacy in creative fields, one that integrates technical fluency with critical and ethical awareness. These insights provide a foundation for more nuanced, culturally sensitive, and ethically grounded approaches to AI adoption in the applied arts.

Informatics in Education
Cyprus University of Technology, University of Cyprus
Quality Education
Openalex Percentile: Top 20%
Art, Technology, and Culture
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Generative AI in the Applied Arts: Workflow Transformations, Evolving Professional Roles, and Emerging Skill Sets — Sonia Andreou, Aekaterini Mavri, et al. · Informatics in Education (2025) | TGRS Research Map | TGRS