Generative Artificial Intelligence in Visual Design Processes for Interactive Multimedia Environments: Analysis of Pipelines and Workflows and Model Proposal
Article Sidebar
Main Article Content
In an era of rapid technological evolution, generative artificial intelligence tools are playing an increasingly important role in visual design processes for multimedia environments. This article examines how these technologies reconfigure traditional 2D design workflows, particularly in interactive contexts, and proposes models that visualize the phases, functions and relationships that emerge from this integration. Through a qualitative and methodological approach based on functional analysis and practical experimentation, different stages of the creative process are documented, from conceptualization to production, exploring how textual instructions (prompts) affect the quality and coherence of the results generated. Specific cases of interaction between designers and generative systems are analyzed, delimiting the tasks assumed by each party, with special emphasis on the functions of ideation, visual iteration and final production. Based on analysis and research, a series of models are proposed that represent collaborative workflows applied to the 2D and 3D multimedia domain with XR, where human and algorithmic agency are strategically articulated. The study provides a structured understanding of the ways in which artificial intelligence not only optimizes time and expands expressive possibilities, but also introduces new challenges in decision-making, authoring and creative formulation. This contribution aims to serve as an analytical and practical reference for design professionals, teachers and researchers interested in contemporary transformations in visual production mediated by generative technologies.
Article Details

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
(c) MARY ANAHI SERNA BERNAL, Jose Luis Rubio Tamayo, 2025
Copyright

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0).
Mary-Anahí Serna-Bernal, Universidad Autónoma de México, UNAM
Mary Anahí Serna Bernal is currently pursuing an M.A. in Visual Design and Communication, specializing in Photography, Audiovisual Media, Multimedia, and Animation, at UNAM, where she investigates the creative use of generative artificial intelligence in video game design. She has enriched her training with a residency at the Interactive and Immersive Communication Laboratory – Ciberimaginario Research Group, within the Department of Audiovisual Communication and Advertising at the Faculty of Communication Sciences of URJC in Madrid, Spain. Under her personal brand Munnamour, she leads branding and multimedia projects. She designed the visual identity and produced digital and multimedia content for the online courses comprising the “Alianza B@UNAM, CCH & ENP ante la pandemia” initiative for UNAM’s high school system. Previously, as head of the Graphic Design Department at IUDM (2018–2019), she maintained the institution’s visual identity by creating social media assets, videos, and large-format print materials, and by managing cultural and sports projects. She has also contributed to documentaries, podcasts, and corporate and cultural campaigns.
Jose-Luis Rubio-Tamayo, Universidad Rey Juan Carlos
Jose Luis Rubio Tamayo is a lecturer in the Faculty of Communication at the URJC and a researcher at the Ciberimaginario Group and the XR Com Lab at the URJC. His areas of specialisation are communication in the extended reality medium, particularly virtual reality, and multimedia and interactive production. Another of the lines of research in which he has specialised is scientific communication and the potential of immersive and interactive technologies for the development of content in this area. He has participated, as a researcher, in several national and international research projects (Crescent, Dominoes, Bio3), as well as in a COST Action (Purple Gain), and has spent time at several universities, such as the UdK in Berlin, the University of Montreal or the University of Porto. He is also the author of more than twenty publications, including articles in indexed journals and book chapters.
Abiri, G. (2024). Generative AI as Digital Media. Harvard Journal of Sport and Entertainment Law, 15(2). https://doi.org/10.2139/ssrn.4878339
Allan, J., Mills, J. y Bradford, N. (2024, octubre 7). Producing Cinematic Content at Scale with a Generative AI-Enabled OpenUSD Pipeline. NVIDIA Technical Blog. https://developer.nvidia.com/blog/producing-cinematic-content-at-scale-with-a-generative-ai-enabled-openusd-pipeline/
Begemann, A. y Hutson, J. (2024). Empirical insights into AI-assisted game development: A case study on the integration of generative AI tools in creative pipelines. Metaverse, 5(2), 2568. https://doi.org/10.54517/m.v5i2.2568
Benjamin, M. (2025, febrero). The Impact of Generative AI on Traditional Graphic Design Workflows [publicación personal].
Bordas, A., Le Masson, P., Thomas, M. y Weil, B. (2024). What is generative in generative artificial intelligence? A design-based perspective. Research in Engineering Design, 35(4), 427–443. https://doi.org/10.1007/s00163-024-00441-x
Bouschery, S. G., Blazevic, V. y Piller, F. T. (2023). Augmenting human innovation teams with artificial intelligence: Exploring transformer-based language models. Journal of Product Innovation Management, 40(2), 139–153. https://doi.org/10.1111/jpim.12656
Buonamici, F., Carfagni, M., Furferi, R., Volpe, Y. y Governi, L. (2020). Generative Design: An Explorative Study. Computer-Aided Design and Applications, 18(1), 144–155. https://doi.org/10.14733/cadaps.2021.144-155
Caballero, J. (2023). Hacia una nueva dimensión del montaje cinematográfico: Explorando las posibilidades de la inteligencia artificial. Hipertext.net, (26), 53-58. https://doi.org/10.31009/hipertext.net.2023.i26.08
Candy, L. y Edmonds, E. (2002). Modeling co-creativity in art and technology. Proceedings of the Fourth Conference on Creativity & Cognition - C&C ’02, 134–141. https://doi.org/10.1145/581710.581731
Candy, L. y Edmonds, E. (2018). Practice-Based Research in the Creative Arts: Foundations and Futures from the Front Line. Leonardo, 51(1), 63–69. https://doi.org/10.1162/LEON_a_01471
Carbonell-Alcocer, A., Sanchez-Acedo, A., Benitez-Aranda, N. y Gertrudix, M. (2024). Impacto de la Inteligencia Artificial Generativa en la eficiencia, calidad e innovación en la producción de Recursos Educativos Abiertos para MOOCS. Comunicación y Sociedad, (2025:22), 1–31. https://doi.org/10.32870/cys.v2025.8784
Castelli, M. y Manzoni, L. (2022). Special Issue: Generative Models in Artificial Intelligence and Their Applications. Applied Sciences, 12(9), 4127. https://doi.org/10.3390/app12094127
Çelik, T. (2024). Generative design experiments with artificial intelligence: Reinterpretation of shape grammar. Open House International, 49(5), 822–842. https://doi.org/10.1108/OHI-04-2023-0079
Cheng, M.-C. y Chou, P.-I. (2015). A Study of the Effect of Creative Thinking Program on Improving Students’ Culinary Creativity. En B. Zhang (Ed.), 2015 2nd International Conference on Creative Education (ICCE 2015), Pt 1 (Vol. 10, pp. 60–64). Singapore Management & Sports Science Inst Pte Ltd.
Clement, M. y Peter, K. (2025, junio). Applied Generative AI: From Pipeline Architecture to Ethical Deployment. [publicación personal].
Correia, A., Jameel, S., Schneider, D., Paredes, H. y Fonseca, B. (2020). A Workflow-Based Methodological Framework for Hybrid Human-AI Enabled Scientometrics. 2020 IEEE International Conference on Big Data (Big Data), 2876–2883. https://doi.org/10.1109/bigdata50022.2020.9378096
Do, H. M., Spear, L. G., Nikpanah, M., Mirmomen, S. M., Machado, L. B., Toscano, A. P., Turkbey, B., Bagheri, M. H., Gulley, J. L. y Folio, L. R. (2020). Augmented Radiologist Workflow Improves Report Value and Saves Time: A Potential Model for Implementation of Artificial Intelligence. Academic Radiology, 27(1), 96–105. https://doi.org/10.1016/j.acra.2019.09.014
Dossabhoy, S. S., Ho, V. T., Ross, E. G., Rodriguez, F. y Arya, S. (2023). Artificial intelligence in clinical workflow processes in vascular surgery and beyond. Seminars in Vascular Surgery, 36(3), 401–412. https://doi.org/10.1053/j.semvascsurg.2023.07.002
Feher, K. (2025). Generative AI, Media, and Society. Taylor & Francis.
Figoli, F., Rampino, L. y Mattioli, F. (2022, June 25). AI in design idea development: A workshop on creativity and human-AI collaboration. En: D. Lockton; S. Lenzi; P. Hekkert; A. Oak; J. Sádaba y P. Lloyd (eds.), DRS Conference, DRS2022, Bilbao, 25 June - 3 July, Bilbao, Spain. https://doi.org/10.21606/drs.2022.414
Fleischmann, K. (2024). Generative Artificial Intelligence in Graphic Design Education: A Student Perspective. Canadian Journal of Learning and Technology, 50(1), 1–17. https://doi.org/10.21432/cjlt28618
Gil, Y. (2009). From Data to Knowledge to Discoveries: Artificial Intelligence and Scientific Workflows. Scientific Programming, 17(3), 167604. https://doi.org/10.3233/SPR-2009-0261
Hubert, K. F., Awa, K. N. y Zabelina, D. L. (2024). The current state of artificial intelligence generative language models is more creative than humans on divergent thinking tasks. Scientific Reports, 14(1), 3440. https://doi.org/10.1038/s41598-024-53303-w
Ibarrola, F., Lawton, T. y Grace, K. (2022). A Collaborative, Interactive and Context-Aware Drawing Agent for Co-Creative Design. arXiv, (arXiv:2209.12588). https://arxiv.org/abs/2209.12588
Jang, Y.-W., Kim, J.-W., Lee, H.-B. y Seo, Y.-H. (2025). Generative AI-driven Graphic Pipeline for Web-based Editing of 4D Volumetric Data. Journal of Web Engineering, 24(01), 135-162. https://doi.org/10.13052/jwe1540-9589.2416
Kamalov, F., Santandreu-Calonge, D., Smail, L., Azizov, D., R. Thadani, D., Kwong, T. y Atif, A. (2025). Evolution of AI in Education: Agentic Workflows. arXiv, (arXiv:2504.20082). https://doi.org/10.48550/arXiv.2504.20082
Kaya-Alpan, Z. B. (2020). A Design Guideline Study for an Inmersive Participatory Urban Design Tool [Tesis de maestría, Bahçeşehir University].
Kulishova, N., Stoliarov, I. y Tsykalo, S. (2024). Decision Making in Process of Board Games Artwork Design Using Generative Artificial Intelligence Applications. Technology and Technique of Typography (Tekhnolohiia I Tekhnika Drukarstva), 1(83), 26–38. https://doi.org/10.20535/2077-7264.1(83).2024.299490
Lai, G., Leymarie, F. F. y Latham, W. (2022). On Mixed-Initiative Content Creation for Video Games. IEEE Transactions on Games, 14(4), 543–557. https://doi.org/10.1109/TG.2022.3176215
Letourneau-Guillon, L., Camirand, D., Guilbert, F. y Forghani, R. (2020). Artificial Intelligence Applications for Workflow, Process Optimization and Predictive Analytics. Neuroimaging Clinics of North America, 30(4), e1–e15. https://doi.org/10.1016/j.nic.2020.08.008
Li, J., Cao, H., Lin, L., Hou, Y., Zhu, R. y El Ali, A. (2024). User Experience Design Professionals’ Perceptions of Generative Artificial Intelligence. Proceedings of the CHI Conference on Human Factors in Computing Systems, article 381, 1–18. https://doi.org/10.1145/3613904.3642114
Li, M. y Chen, Y. (2022). Using Artificial Intelligence Assisted Learning Technology on Augmented Reality-Based Manufacture Workflow. Frontiers in Psychology, 13. https://doi.org/10.3389/fpsyg.2022.859324
Lin, Z., Ehsan, U., Agarwal, R., Dani, S., Vashishth, V. y Riedl, M. (2023). Beyond Prompts: Exploring the Design Space of Mixed-Initiative Co-Creativity Systems. arXiv (arXiv:2305.07465). https://doi.org/10.48550/arXiv.2305.07465
Lin, Z. y Riedl, M. (2023). An Ontology of Co-Creative AI Systems. arXiv (arXiv:2310.07472). https://doi.org/10.48550/arXiv.2310.07472
Liu, C. (2022). Artificial Intelligence Interactive Design System Based on Digital Multimedia Technology. Advances in Multimedia, 2022(1), 4679066. https://doi.org/10.1155/2022/4679066
Liu, Y. (2023). Implications of generative artificial intelligence for the development of the media industry. Advances in Engineering Innovation, 1(1), 28–35. https://doi.org/10.54254/2977-3903/1/2023006
Lively, J., Hutson, J. y Melick, E. (2023). Integrating AI-Generative Tools in Web Design Education: Enhancing Student Aesthetic and Creative Copy Capabilities Using Image and Text-Based AI Generators. DS Journal of Artificial Intelligence and Robotics, 1(1), 23–36. https://doi.org/10.59232/AIR-V1I1P103
McCormack, J., Gifford, T. y Hutchings, P. (2019). Autonomy, Authenticity, Authorship and Intention in computer generated art. arXiv (arXiv:1903.02166). https://doi.org/10.48550/arXiv.1903.02166
Mohammadabadi, S. M. S. (2025). From Generative AI to Innovative AI: An Evolutionary Roadmap. arXiv (arXiv:2503.11419). https://doi.org/10.48550/arXiv.2503.11419
Moreno-Sánchez, D., Moreno-Nieto, D., Burgos-Pintos, P. y Molina, S. I. (2024). Artificial Intelligence in the Design Workflow. Review of Tools with Special Focus on Additive Manufacturing. En C. Manchado del Val, M. Suffo-Pino, R. Miralbes-Buil, D. Moreno-Sánchez, y D. Moreno-Nieto (Eds.), Advances in Design Engineering IV (pp. 468–475). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-51623-8_45
Mortazavi, A. (2023). Enhancing User Experience Design workflow with Artificial Intelligence tools [Tesis de maestría. Linköping University, Suecia]. https://www.diva-portal.org/smash/get/diva2:1800706/FULLTEXT01.pdf
Park, Y. y Yun, J. Y. (2021). A Design Case Study of Artificial Intelligence Pipeline Visualization. Archives of Design Research, 34(1), 133–155. https://doi.org/10.15187/adr.2021.02.34.1.133
Patel, K., Beeram, D., Ramamurthy, P., Garg, P. y Kumar, S. (2024). Ai-Enhanced Design: Revolutionizing Methodologies and Workflows. Intelligence Research and Development, 2(1), 135-157. https://iaeme.com/Home/article_id/IJAIRD_02_01_013
Rico-Sesé, J. (2023). Nuevos retos para el diseño y la comunicación. La inteligencia artificial en los procesos creativos del diseño gráfico. [Tesis doctoral, Universitat Politècnica de València]. https://doi.org/10.4995/Thesis/10251/192876
Rubio-Tamayo, J. L., Wuebben, D. L. y Gertrudix, M. (2024). Standards for science communication in extended and virtual reality: A model for XR/VR based on London Charter and Seville Principles. Journal of Science Communication, 23(3), A03. https://doi.org/10.22323/2.23030203
Rubio-Tamayo, J. L., Gertrudix, M. y Wuebben, D. (2025). Immersive Scientific Communication: A Multidimensional Theoretical Model for Approaching Extended Reality as a Medium. Presence: Virtual and Augmented Reality, 34, 135–157. https://doi.org/10.1162/pres_a_00444
Saadi, J. I. y Yang, M. C. (2023). Generative Design: Reframing the Role of the Designer in Early-Stage Design Process. Journal of Mechanical Design, 145(4), 041411. https://doi.org/10.1115/1.4056799
Sadeghi, A. H., Maat, A. P. W. M., Taverne, Y. J. H. J., Cornelissen, R., Dingemans, A.-M. C., Bogers, A. J. J. C. y Mahtab, E. A. F. (2021). Virtual reality and artificial intelligence for 3-dimensional planning of lung segmentectomies. JTCVS Techniques, 7, 309–321. https://doi.org/10.1016/j.xjtc.2021.03.016
Sakirin, T. y Kusuma, S. (2023). A Survey of Generative Artificial Intelligence Techniques. Babylonian Journal of Artificial Intelligence, 2023, 10–14. https://doi.org/10.58496/BJAI/2023/003
Sapkota, R., Roumeliotis, K. I. y Karkee, M. (2025). AI Agents vs. Agentic AI: A Conceptual Taxonomy, Applications and Challenges. arXiv (arXiv:2505.10468). https://doi.org/10.48550/arXiv.2505.10468
Sattele, V., Reyes, M. y Fonseca, A. (2023). La Inteligencia Artificial Generativa en el Proceso Creativo y en el Desarrollo de Conceptos de Diseño. Umática. Revista sobre Creación y Análisis de la Imagen, 6. https://doi.org/10.24310/umatica.2023.v5i6.17153
Schneider, Á. y Csűrös, D. (2025, Mayo 12). Towards Distributed Creativity: Understanding Generative AI in the Context of Design Philosophy and the Material Turn. En M. Karyda, D. Çay, Á. Bakk, R. Dezső y J. Hemmings, (eds.), Data as Experiential Knowledge and Embodied Processes (pp. 12-13). https://doi.org/10.21606/eksig2025.127
Sengar, S. S., Hasan, A. B., Kumar, S. y Carroll, F. (2024). Generative artificial intelligence: A systematic review and applications. Multimedia Tools and Applications, 84, 23661–23700. https://doi.org/10.1007/s11042-024-20016-1
Serna M., E., Acevedo M., E. y Serna A., A. (2019). Integration of properties of virtual reality, artificial neural networks, and artificial intelligence in the automation of software tests: A review. Journal of Software: Evolution and Process, 31(7). https://doi.org/10.1002/smr.2159
Serra, G. (2024). Integration of AI Tools In The Product Design Workflow. [Tesis de maestría, University of Twente, Holanda]. https://essay.utwente.nl/fileshare/file/103483/Serra_MA_Engineering%20Technology.pdf
Spinner, T., Schlegel, U., Schafer, H. y El-Assady, M. (2019). explAIner: A Visual Analytics Framework for Interactive and Explainable Machine Learning. IEEE Transactions on Visualization and Computer Graphics, 26(1), 1064-1074. https://doi.org/10.1109/tvcg.2019.2934629
Subramonyam, H., Thakkar, D., Ku, A., Dieber, J. y Sinha, A. K. (2025). Prototyping with Prompts: Emerging Approaches and Challenges in Generative AI Design for Collaborative Software Teams. Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems, article 882, 1–22. https://doi.org/10.1145/3706598.3713166
Suyanto, M. y Wibowo, F. W. (2018). Animation opportunities of intelligent multimedia systems in developing a creative economy park. 2018 International Conference on Information and Communications Technology (ICOIACT), 72–77. https://doi.org/10.1109/ICOIACT.2018.8350826
Tammisto, E. (2025). Usage of Artificial Intelligence in Industrial Design Processes. [Tesis de maestría. Lappeenranta–Lahti University of Technology LUT, Finlandia]. https://lutpub.lut.fi/bitstream/handle/10024/169011/Diplomityo_Tammisto_Esa.pdf?sequence=3&isAllowed=y
Venkata, K. (2025). Optimizing Data Pipelines for Generative AI Workflows: Challenges and Best Practices. International Journal on Science and Technology, 16(1), 1527. https://doi.org/10.71097/IJSAT.v16.i1.1527
Wang, C. y Chung, J. (2023). A Study of Artificial Intelligence Generated 3D Engine Animation Workflow. International Journal of Advanced Smart Convergence, 12(4), 286–292. https://doi.org/10.7236/IJASC.2023.12.4.286
Wang, W.-F., Lu, C.-T., Ponsa-i-Campanyà, N., Chen, B.-Y. y Chen, M. Y. (2025). AIdeation: Designing a Human-AI Collaborative Ideation System for Concept Designers. Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems, article 21, 1–28. https://doi.org/10.1145/3706598.3714148
Wilde, L. R. A. (2023). Generative Imagery as Media Form and Research Field: Introduction to a New Paradigm. Image, 19(1) 6-33. https://doi.org/10.25969/MEDIAREP/22326
Wilson, R. (2023). The Host in the Machine; How Ai Is Influencing Content Production: TVB Europe. TVB Europe, 54–55. https://www.tvbeurope.com/business/tvbeurope-releases-may-2023-issue
Winkler-Schwartz, A., Bissonnette, V., Mirchi, N., Ponnudurai, N., Yilmaz, R., Ledwos, N., Siyar, S., Azarnoush, H., Karlik, B. y Del Maestro, R. F. (2019). Artificial Intelligence in Medical Education: Best Practices Using Machine Learning to Assess Surgical Expertise in Virtual Reality Simulation. Journal of Surgical Education, 76(6), 1681–1690. https://doi.org/10.1016/j.jsurg.2019.05.015
Yannakakis, G. N., Liapis, A. y Alexopoulos, C. (2014). Mixed-Initiative Co-Creativity. En 9th International Conference on the Foundations of Digital Games, Fort Lauderdale. 1-8. https://www.um.edu.mt/library/oar//handle/123456789/29459
Yuan, P. F., Yao, J., Yan, C., Wang, X. y Leach, N. (Eds.). (2021). Proceedings of the 2020 DigitalFUTURES: The 2nd International Conference on Computational Design and Robotic Fabrication (CDRF 2020). Springer Singapore. https://doi.org/10.1007/978-981-33-4400-6
Zhang, Z., Wen, F., Sun, Z., Guo, X., He, T. y Lee, C. (2022). Artificial Intelligence-Enabled Sensing Technologies in the 5G/Internet of Things Era: From Virtual Reality/Augmented Reality to the Digital Twin. Advanced Intelligent Systems, 4(7), 2100228. https://doi.org/10.1002/aisy.202100228
Zhou, J., Li, R., Tang, J., Tang, T., Li, H., Cui, W. y Wu, Y. (2024). Understanding Nonlinear Collaboration between Human and AI Agents: A Co-design Framework for Creative Design. arXiv ( arXiv:2401.07312). https://doi.org/10.48550/arXiv.2401.07312
Zhou, Z., Jin, J., Phadnis, V., Yuan, X., Jiang, J., Qian, X., Wright, K., Sherwood, M., Mayes, J., Zhou, J., Huang, Y., Xu, Z., Zhang, Y., Lee, J., Olwal, A., Kim, D., Iyengar, R., Li, N. y Du, R. (2025). InstructPipe: Generating Visual Blocks Pipelines with Human Instructions and LLMs. Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems, article 877, 1–22. https://doi.org/10.1145/3706598.3713905
Zhu, W., Wang, X. y Gao, W. (2020). Multimedia Intelligence: When Multimedia Meets Artificial Intelligence. IEEE Transactions on Multimedia, 22(7), 1823–1835. https://doi.org/10.1109/TMM.2020.2969791
Zhu, Z., Lee, H., Pan, Y. y Cai, P. (2024). AI assistance in enterprise UX design workflows: Enhancing design brief creation for designers. Frontiers in Artificial Intelligence, 7, 1404647. https://doi.org/10.3389/frai.2024.1404647