Application of AI in the Creative Process: Case Study in the Design Industry
Abstract
The design industry has undergone significant transformations with the advent of Artificial Intelligence (AI), influencing the creative process in various ways. Despite its growing integration, the extent to which AI enhances creativity in design remains under-explored. This study aims to investigate the application of AI tools in the creative processes of designers, with a focus on identifying their impact on innovation, efficiency, and problem-solving. The research employs a qualitative case study approach, analyzing multiple design projects that incorporate AI tools, including generative design software and AI-driven prototyping systems. Data was collected through interviews with designers and observations of their workflows, supplemented by project outcome analyses. The results indicate that AI tools provide designers with new perspectives, automate repetitive tasks, and accelerate ideation, leading to increased productivity and innovative solutions. However, challenges such as the need for proper training and concerns about AI replacing human creativity were also noted. The study concludes that while AI enhances the creative process, it should be seen as a complement to human ingenuity rather than a replacement. Designers who effectively integrate AI tools into their workflows experience enhanced creativity, though a balance must be maintained between machine-driven processes and human judgment.
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References
Abd, H., & König, A. (2020). A Compact Four Transistor CMOS-Design of a Floating Memristor for Adaptive Spiking Neural Networks and Corresponding Self-X Sensor Electronics to Industry 4.0. Tm - Technisches Messen, 87(s1), s91–s96. https://doi.org/10.1515/teme-2020-0024
Abduljabbar, R., Dia, H., Liyanage, S., & Bagloee, S. A. (2019). Applications of Artificial Intelligence in Transport: An Overview. Sustainability, 11(1), 189. https://doi.org/10.3390/su11010189
Accorsi, R., Baruffaldi, G., & Manzini, R. (2020). A closed-loop packaging network design model to foster infinitely reusable and recyclable containers in food industry. Sustainable Production and Consumption, 24, 48–61. https://doi.org/10.1016/j.spc.2020.06.014
Akoury, C. (2020). Apprehending the Creative Process through Drawing in the Foundation Design Studio. International Journal of Art & Design Education, 39(1), 113–125. https://doi.org/10.1111/jade.12223
Alimadadi, A., Aryal, S., Manandhar, I., Munroe, P. B., Joe, B., & Cheng, X. (2020). Artificial intelligence and machine learning to fight COVID-19. Physiological Genomics, 52(4), 200–202. https://doi.org/10.1152/physiolgenomics.00029.2020
Antonopoulos, I., Robu, V., Couraud, B., Kirli, D., Norbu, S., Kiprakis, A., Flynn, D., Elizondo-Gonzalez, S., & Wattam, S. (2020). Artificial intelligence and machine learning approaches to energy demand-side response: A systematic review. Renewable and Sustainable Energy Reviews, 130, 109899. https://doi.org/10.1016/j.rser.2020.109899
Azizi, A. (2020). Applications of Artificial Intelligence Techniques to Enhance Sustainability of Industry 4.0: Design of an Artificial Neural Network Model as Dynamic Behavior Optimizer of Robotic Arms. Complexity, 2020, 1–10. https://doi.org/10.1155/2020/8564140
Brinks, V. (2019). ‘And Since I Knew About the Possibilities There …’: The Role of Open Creative Labs in User Innovation Processes. Tijdschrift Voor Economische En Sociale Geografie, 110(4), 381–394. https://doi.org/10.1111/tesg.12353
Cioffi, R., Travaglioni, M., Piscitelli, G., Petrillo, A., & De Felice, F. (2020). Artificial Intelligence and Machine Learning Applications in Smart Production: Progress, Trends, and Directions. Sustainability, 12(2), 492. https://doi.org/10.3390/su12020492
De Garrido, L., Gómez Sanz, J., & Pavón, J. (2019). Agent-based modeling of collaborative creative processes with INGENIAS. AI Communications, 32(3), 223–233. https://doi.org/10.3233/AIC-190618
Di Vaio, A., Palladino, R., Hassan, R., & Escobar, O. (2020). Artificial intelligence and business models in the sustainable development goals perspective: A systematic literature review. Journal of Business Research, 121, 283–314. https://doi.org/10.1016/j.jbusres.2020.08.019
Dobrza?ski, L. A., & Dobrza?ski, L. B. (2020). Approach to the Design and Manufacturing of Prosthetic Dental Restorations According to the Rules of Industry 4.0. Materials Performance and Characterization, 9(1), 394–476. https://doi.org/10.1520/MPC20200020
Dordlofva, C. (2020). A Design for Qualification Framework for the Development of Additive Manufacturing Components—A Case Study from the Space Industry. Aerospace, 7(3), 25. https://doi.org/10.3390/aerospace7030025
Goralski, M. A., & Tan, T. K. (2020). Artificial intelligence and sustainable development. The International Journal of Management Education, 18(1), 100330. https://doi.org/10.1016/j.ijme.2019.100330
Guzman, A. L., & Lewis, S. C. (2020). Artificial intelligence and communication: A Human–Machine Communication research agenda. New Media & Society, 22(1), 70–86. https://doi.org/10.1177/1461444819858691
Haenlein, M., & Kaplan, A. (2019). A Brief History of Artificial Intelligence: On the Past, Present, and Future of Artificial Intelligence. California Management Review, 61(4), 5–14. https://doi.org/10.1177/0008125619864925
Holzmann, P., Breitenecker, R. J., Schwarz, E. J., & Gregori, P. (2020). Business model design for novel technologies in nascent industries: An investigation of 3D printing service providers. Technological Forecasting and Social Change, 159, 120193. https://doi.org/10.1016/j.techfore.2020.120193
Ivancovsky, T., Shamay-Tsoory, S., Lee, J., Morio, H., & Kurman, J. (2019). A dual process model of generation and evaluation: A theoretical framework to examine cross-cultural differences in the creative process. Personality and Individual Differences, 139, 60–68. https://doi.org/10.1016/j.paid.2018.11.012
Jablon-Roberts, S., & Sanders, E. (2019). A Theoretical Framework for the Creative Process of Theatrical Costume Design for Historically Set Productions. Clothing and Textiles Research Journal, 37(1), 35–50. https://doi.org/10.1177/0887302X18796320
Jana, A., Paul, R., & Roy, A. K. (2019). Architectural design and promises of carbon materials for energy conversion and storage: In laboratory and industry. In Carbon Based Nanomaterials for Advanced Thermal and Electrochemical Energy Storage and Conversion (pp. 25–61). Elsevier. https://doi.org/10.1016/B978-0-12-814083-3.00002-0
Jha, K., Doshi, A., Patel, P., & Shah, M. (2019). A comprehensive review on automation in agriculture using artificial intelligence. Artificial Intelligence in Agriculture, 2, 1–12. https://doi.org/10.1016/j.aiia.2019.05.004
Kakani, V., Nguyen, V. H., Kumar, B. P., Kim, H., & Pasupuleti, V. R. (2020). A critical review on computer vision and artificial intelligence in food industry. Journal of Agriculture and Food Research, 2, 100033. https://doi.org/10.1016/j.jafr.2020.100033
Lalmuanawma, S., Hussain, J., & Chhakchhuak, L. (2020). Applications of machine learning and artificial intelligence for Covid-19 (SARS-CoV-2) pandemic: A review. Chaos, Solitons & Fractals, 139, 110059. https://doi.org/10.1016/j.chaos.2020.110059
Langlotz, C. P., Allen, B., Erickson, B. J., Kalpathy-Cramer, J., Bigelow, K., Cook, T. S., Flanders, A. E., Lungren, M. P., Mendelson, D. S., Rudie, J. D., Wang, G., & Kandarpa, K. (2019). A Roadmap for Foundational Research on Artificial Intelligence in Medical Imaging: From the 2018 NIH/RSNA/ACR/The Academy Workshop. Radiology, 291(3), 781–791. https://doi.org/10.1148/radiol.2019190613
Lettori, J., Raffaeli, R., Peruzzini, M., Schmidt, J., & Pellicciari, M. (2020). Additive manufacturing adoption in product design: An overview from literature and industry. Procedia Manufacturing, 51, 655–662. https://doi.org/10.1016/j.promfg.2020.10.092
London, A. J. (2019). Artificial Intelligence and Black?Box Medical Decisions: Accuracy versus Explainability. Hastings Center Report, 49(1), 15–21. https://doi.org/10.1002/hast.973
Nadarzynski, T., Miles, O., Cowie, A., & Ridge, D. (2019). Acceptability of artificial intelligence (AI)-led chatbot services in healthcare: A mixed-methods study. DIGITAL HEALTH, 5, 2055207619871808. https://doi.org/10.1177/2055207619871808
Pourjavad, E., & Mayorga, R. V. (2019). An optimization model for network design of a closed-loop supply chain: A study for a glass manufacturing industry. International Journal of Management Science and Engineering Management, 14(3), 169–179. https://doi.org/10.1080/17509653.2018.1512387
Prabhu, R., Bracken, J., Armstrong, C. B., Jablokow, K., Simpson, T. W., & Meisel, N. A. (2020). Additive creativity: Investigating the use of design for additive manufacturing to encourage creativity in the engineering design industry. International Journal of Design Creativity and Innovation, 8(4), 198–222. https://doi.org/10.1080/21650349.2020.1813633
Price, R. A., De Lille, C., & Bergema, K. (2019). Advancing Industry through Design: A Longitudinal Case Study of the Aviation Industry. She Ji: The Journal of Design, Economics, and Innovation, 5(4), 304–326. https://doi.org/10.1016/j.sheji.2019.07.003
Rajaee, T., Ebrahimi, H., & Nourani, V. (2019). A review of the artificial intelligence methods in groundwater level modeling. Journal of Hydrology, 572, 336–351. https://doi.org/10.1016/j.jhydrol.2018.12.037
Saris, B. (2020). A Review of Engagement with Creativity and Creative Design Processes for Visual Communication Design (VCD) Learning in China. International Journal of Art & Design Education, 39(2), 306–318. https://doi.org/10.1111/jade.12262
Stuhlfaut, M. W., & Windels, K. (2019). Altered states: The effects of media and technology on the creative process in advertising agencies. Journal of Marketing Communications, 25(1), 1–27. https://doi.org/10.1080/13527266.2017.1380069
Trochu, J., Chaabane, A., & Ouhimmou, M. (2020). A carbon-constrained stochastic model for eco-efficient reverse logistics network design under environmental regulations in the CRD industry. Journal of Cleaner Production, 245, 118818. https://doi.org/10.1016/j.jclepro.2019.118818
Tussyadiah, I. (2020). A review of research into automation in tourism: Launching the Annals of Tourism Research Curated Collection on Artificial Intelligence and Robotics in Tourism. Annals of Tourism Research, 81, 102883. https://doi.org/10.1016/j.annals.2020.102883
Ullah, Z., Al-Turjman, F., Mostarda, L., & Gagliardi, R. (2020). Applications of Artificial Intelligence and Machine learning in smart cities. Computer Communications, 154, 313–323. https://doi.org/10.1016/j.comcom.2020.02.069
Vaishya, R., Javaid, M., Khan, I. H., & Haleem, A. (2020). Artificial Intelligence (AI) applications for COVID-19 pandemic. Diabetes & Metabolic Syndrome: Clinical Research & Reviews, 14(4), 337–339. https://doi.org/10.1016/j.dsx.2020.04.012
Wirtz, B. W., Weyerer, J. C., & Geyer, C. (2019). Artificial Intelligence and the Public Sector—Applications and Challenges. International Journal of Public Administration, 42(7), 596–615. https://doi.org/10.1080/01900692.2018.1498103
Yin, Y., & Qin, S. (2019). A smart performance measurement approach for collaborative design in Industry 4.0. Advances in Mechanical Engineering, 11(1), 1687814018822570. https://doi.org/10.1177/1687814018822570
Zhang, X., & Wen, K.-H. (2020). A Model Process of Integrating Context of Local Culture for Pre-Development Stage in the Design of Cultural and Creative Products—Using Macao’s Historical Buildings as an Example. Sustainability, 12(15), 6263. https://doi.org/10.3390/su12156263
Zhao, L., Dai, T., Qiao, Z., Sun, P., Hao, J., & Yang, Y. (2020). Application of artificial intelligence to wastewater treatment: A bibliometric analysis and systematic review of technology, economy, management, and wastewater reuse. Process Safety and Environmental Protection, 133, 169–182. https://doi.org/10.1016/j.psep.2019.11.014
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