Creativity: Empowered or at Risk? Designers’ Perceptions of the Generative Artificial Intelligence Paradox in Visual Identity Design

Ana Sofia Ferreira de Almeida; Catarina Lélis; Diogo Gomes

doi:10.34624/jdmi.v9i21.41120

Authors

Ana Sofia Ferreira de Almeida University of Aveiro
Catarina Lélis University of Aveiro
Diogo Gomes University of Aveiro

DOI:

https://doi.org/10.34624/jdmi.v9i21.41120

Keywords:

Generative Artificial Intelligence, Creativity, Design, Visual Identity, Human-AI Collaboration

Abstract

Generative Artificial Intelligence (GAI) is reshaping visual identity (VI) design, exposing a paradox between creative empowerment and risk. This study explores how designers perceive the integration of GAI into their work and what implications they anticipate for professional practice. A mixed methodology was used through an online survey, obtaining 180 valid responses from design professionals. The results indicate widespread familiarity and adoption, with a consistent perception of efficiency gains and usefulness in the process, as well as contributions to exploration and personalization (e.g., adaptive palettes and typographies, cocreation with clients, generative brand experiences). At the same time, reservations remain regarding originality/authorship, copyright and intellectual property (IP), technological dependence, and aesthetic homogenization. The prevailing view is that AI will complement, not replace, human creativity, requiring skills in AI-assisted workflows and human-centred creative direction. It is concluded that the impact of AI is conditionally empowering and depends on its management in the creative process and on training that integrates AI literacy, ethics, and IP.

References

Adeleye, I. O. (2024). The Impact of Artificial Intelligence on Design: Enhancing Creativity and Efficiency. Journal of Engineering and Applied Sciences, 3(1), 1–14. https://doi.org/10.70560/VVSFEJ12

Arcas, B. A. y. (2017). Art in the Age of Machine Intelligence. Arts 2017, Vol. 6, Page 18, 6(4), 18. https://doi.org/10.3390/ARTS6040018

Braun, V., & and Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa

Brown, T. B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., Agarwal, S., Herbert-Voss, A., Krueger, G., Henighan, T., Child, R., Ramesh, A., Ziegler, D. M., Wu, J., Winter, C., … Amodei, D. (2020). Language Models are Few-Shot Learners. Advances in Neural Information Processing Systems, 2020-December. https://arxiv.org/pdf/2005.14165

Bryman, A. (2012). Social Research Methods (Oxford University Press, Ed.; Fourth Edition).

Costa, J. (2008). A Imagem da Marca. Um fenômeno Social (Rosari, Ed.).

Creswell, J. W. (2008). Research Design Qualitative, Quantitative, and Mixed Methods Approaches (I. SAGE Publications, Ed.; 3rd edition).

Domingos, P. (2017). A Revolução do Algoritmo-Mestre.

Fields, Z. (2023). Human and Artificial Creativity. Https://Services.Igi-Global.Com/Resolvedoi/Resolve.Aspx?Doi=10.4018/978-1-6684-6366-6.Ch001, 1–18. https://doi.org/10.4018/978-1-6684-6366-6.CH001

Garcia, M. B. (2024). The Paradox of Artificial Creativity: Challenges and Opportunities of Generative AI Artistry. Creativity Research Journal. https://doi.org/10.1080/10400419.2024.2354622

Hansen, S. M. (2023). A Model for Understanding the Evolving Role of Graphic Designers in the Era of Artificial Intelligence. https://doi.org/10.22501/HUB.2156238

Hwang, J., Kim, H., & Kim, H. M. (2023). Relationships among memorable brand experience, brand preference, and behavioral intentions: focusing on the difference between robot servers and human servers. Journal of Hospitality and Tourism Technology, 14(3), 430–443. https://doi.org/10.1108/JHTT-09-2021-0254/FULL/PDF

Kara, H. (2022). Qualitative Research for Quantitative Researchers (A. Owen, H. Cavender-Deere, & C. Marke, Eds.). Sage Publications Ltd.

Kotler, P., Kartajaya, H., & Setiawan, I. (2017). Marketing 4.0_ Moving from Traditional to Digital (Wiley, Ed.).

Liu, Z. (2025). Human-AI Co-Creation: A Framework for Collaborative Design in Intelligent Systems. AHFE, 2025, 2025. https://doi.org/10.48550/arXiv.2507.17774

McCormack, J., Hutchings, P., Gifford, T., Yee-King, M., Llano, M. T., & D’Inverno, M. (2020). Design considerations for real-time collaboration with creative artificial intelligence. Organised Sound, 25(1), 41–52. https://doi.org/10.1017/S1355771819000451

Norvig, P., & Russell, S. (2020). Artificial Intelligence: A Modern Approach (Pearson, Ed.; 4th Edition).

Runco, M. A. (2025). Updating the Standard Definition of Creativity to Account for the Artificial Creativity of AI. Creativity Research Journal, 37(1), 1–5. https://doi.org/10.1080/10400419.2023.2257977

Sá, P., Costa, A. P., & Moreira, A. (2021). Reflexões em torno de Metodologias de Investigação: recolha de dados: Vol. Volume 2 (Universidade de Aveiro, Ed.). https://doi.org/10.34624/ka02-fq42

Zheng, R. (2023). Brand Visual Model Design Based on Artificial Intelligence and Digital Technology. 2nd IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics, ICDCECE 2023. https://doi.org/10.1109/ICDCECE57866.2023.10151201