REINVENTING DIGITAL ILLUSTRATION WITH GENERATIVE AI TOOLS
DOI:
https://doi.org/10.29121/shodhkosh.v6.i5s.2025.6876Keywords:
Generative AI, Digital Illustration, Diffusion Models, Human–AI Collaboration, Aesthetic Evaluation, Creative Performance Index (CPI)Abstract [English]
The advancement of digital illustration has led to a revolution stage whereby it entails the application of generative artificial intelligence which integrates the human creativity and the computational creativity. In this paper, the shift towards generative ecosystems via models such as GANs, VAEs, and diffusion networks will be considered in relation to the transformation of the conventional workflows of vectors and raster. It suggests an ambivalent framework based on which the illustration is regarded as a multidimensional contact between human mental will and machine learning inference. In order to estimate the similarity of artwork produced with the help of AI and human-produced artworks in terms of the aesthetic and semantic quality, the paper proposes a Creative Performance Index (CPI) as a critical combination of Fréchet Inception Distance (FID) and CLIP Score and the human-based measurements of originality and emotional resonance. Through a number of case studies of applications like DALLE, Stable Diffusion and Midjourney, it has been demonstrated in the paper that coaching of human feedback based on an iteration approach has a profound impact on artistic containment and richness of ideas. The findings validate that generative AI does not replace the agency of the illustrator but expands it to make the creative process adaptive and symbiotic system of leading to ideas, contemplating on them, and perfecting them.
References
Albar Mansoa, P. J. (2024). Artificial Intelligence for Image Generation in Art: How Does It Impact on the Future of Fine Art Students? Encuentros, 20, 145–164.
AlGerafi, M. A., Zhou, Y., Alfadda, H., and Wijaya, T. T. (2023). Understanding the Factors Influencing Higher Education Students’ Intention to Adopt Artificial Intelligence-Based Robots. IEEE Access, 11, 99752–99764. https://doi.org/10.1109/ACCESS.2023.3310109 DOI: https://doi.org/10.1109/ACCESS.2023.3314499
Avlonitou, C., and Papadaki, E. (2025). AI: An Active and Innovative Tool for Artistic Creation. Arts, 14, 52. https://doi.org/10.3390/arts14030052 DOI: https://doi.org/10.3390/arts14030052
Bartlett, K. A., and Camba, J. D. (2024). Generative Artificial Intelligence in Product Design Education: Navigating Concerns of Originality and Ethics. International Journal of Interactive Multimedia and Artificial Intelligence, 8, 55–64. https://doi.org/10.9781/ijimai.2024.02.004 DOI: https://doi.org/10.9781/ijimai.2024.02.006
Baudoux, G. (2024). The Benefits and Challenges of AI Image Generators for Architectural Ideation: Study of an Alternative Human–Machine Co-Creation Exchange Based on Sketch Recognition. International Journal of Architectural Computing, 22, 201–215. https://doi.org/10.1177/14780771231208340 DOI: https://doi.org/10.1177/14780771241253438
Bhargava, R., Williams, D., and D’Ignazio, C. (2021). How Learners Sketch Data Stories. In Proceedings of the 2021 IEEE Visualization Conference (VIS) (pp. 196–200). IEEE. DOI: https://doi.org/10.1109/VIS49827.2021.9623299
Demartini, C. G., Sciascia, L., Bosso, A., and Manuri, F. (2024). Artificial Intelligence Bringing Improvements to Adaptive Learning in Education: A Case Study. Sustainability, 16, 1347. https://doi.org/10.3390/su16031347 DOI: https://doi.org/10.3390/su16031347
De Winter, J. C. F., Dodou, D., and Stienen, A. H. A. (2023). ChatGPT in Education: Empowering Educators Through Methods for Recognition and Assessment. Informatics, 10, 87. https://doi.org/10.3390/informatics10040087 DOI: https://doi.org/10.3390/informatics10040087
Donnici, G., Galiè, G., and Frizziero, L. (2025). Rethinking Sketching: Integrating Hand Drawings, Digital Tools, and AI in Modern Design. Designs, 9, 119. https://doi.org/10.3390/designs9050119 DOI: https://doi.org/10.3390/designs9050119
Li, P., Li, B., and Li, Z. (2024). Sketch-to-Architecture: Generative AI-Aided Architectural Design. arXiv. https://arxiv.org/abs/2403.20186
Morales-Chan, M. A. (2023). Explorando el Potencial de ChatGPT: Una Clasificación de Prompts Efectivos para la Enseñanza. Universidad Galileo.
Ning, Y., Zhang, C., Xu, B., Zhou, Y., and Wijaya, T. T. (2024). Teachers’ AI-TPACK: Exploring the Relationship Between Knowledge Elements. Sustainability, 16, 978. https://doi.org/10.3390/su16030978 DOI: https://doi.org/10.3390/su16030978
Relmasira, S. C., Lai, Y. C., and Donaldson, J. P. (2023). Fostering AI Literacy in Elementary Science, Technology, Engineering, Art, and Mathematics (STEAM) Education in the Age of Generative AI. Sustainability, 15, 13595. https://doi.org/10.3390/su151813595 DOI: https://doi.org/10.3390/su151813595
Rodrigues, O. S., and Rodrigues, K. S. (2023). A Inteligência Artificial na Educação: Os Desafios do ChatGPT. Texto Livre, 16, e45997. https://doi.org/10.35699/1983-3652.2023.45997 DOI: https://doi.org/10.1590/1983-3652.2023.45997
Sáez-Velasco, S., Alaguero-Rodríguez, M., Delgado-Benito, V., and Rodríguez-Cano, S. (2024). Analysing the Impact of Generative AI in Arts Education: A Cross-Disciplinary Perspective of Educators and Students in Higher Education. Informatics, 11, 37. https://doi.org/10.3390/informatics11020037 DOI: https://doi.org/10.3390/informatics11020037
Wang, Y., and Yang, S. (2024). Constructing and Testing AI International Legal Education Coupling-Enabling Model. Sustainability, 16, 1524. https://doi.org/10.3390/su16041524 DOI: https://doi.org/10.3390/su16041524
Zhou, Y., and Park, H. J. (2023). An AI-Augmented Multimodal Application for Sketching Out Conceptual Design. International Journal of Architectural Computing, 21, 565–580. https://doi.org/10.1177/14780771231170065 DOI: https://doi.org/10.1177/14780771221147605
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Copyright (c) 2025 Dr. Sonia Riyat, Dr. Jay Gandhi, Amit Kumar, Dr. Kaberi Das, Abhijeet Panigrahy, D. Jennifer, Omkar Mahesh Manav
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