STRATEGIC MANAGEMENT OF AI ART EXHIBITIONS
DOI:
https://doi.org/10.29121/shodhkosh.v6.i3s.2025.6818Keywords:
AI Art Exhibition, Management of Culture, Strategic Planning, Digital Curation, Interactions With Audience, Technological InnovationAbstract [English]
The art of AI exhibitions management is an emerging area of frontier by the array of technology, imagination, and culture administration. The emergence of artificial intelligence as a driver in the production of art has introduced new issues and opportunities to curators and managers regarding how to conceptualize, organize and maintain exhibitions dealing with the issue of algorithmic creativity. This study indicates that AI art exhibitions should be managed in a comprehensive manner that addresses the strategic management of art exhibitions, their curation, operations, and the audience. It begins by defining the scope of AI art and contextualising it within the context of bigger conversations on digital culture and innovation management. The framework focuses on creating effective visions, missions, and goals that outline the value and the meaning of AI-based experiences of art. Through market and audience analysis, institutions will be in a better position to have a clear vision of the new demands and position themselves in the competitive arena of the cultural sector. The essence of successful exhibition curation consists in the developed concept of AI-based works selection principles including ethical considerations, aesthetic characteristics, collaboration trends that can unite artists, technologists, and curators. The operational strategies prove the need of the good technological foundation, the effective resource allocation, and the active risk management, particularly taking into account the fact that AI systems can be described as dynamic and experimental. The marketing strategies such as the narrative based branding and the cooperation with the digital media and the immersion of the audiences also precondition the rise of the degree of the public interest.
References
Adahl, S., and Träskman, T. (2024). Archeologies of Future Heritage: Cultural Heritage, Research Creations, and Youth. Mimesis Journal, 13, 487–497.
Barath, C.-V., Logeswaran, S., Nelson, A., Devaprasanth, M., and Radhika, P. (2023). AI in Art Restoration: A Comprehensive Review of Techniques, Case Studies, Challenges, and Future Directions. International Research Journal of Modern Engineering and Technology Science, 5, 16–21.
Bonacini, E., and Giaccone, S. C. (2022). Gamification and Cultural Institutions in Cultural Heritage Promotion: A Successful Example from Italy. Cultural Trends, 31, 3–22. https://doi.org/10.1080/09548963.2021.1910490 DOI: https://doi.org/10.1080/09548963.2021.1910490
Chang, L. (2021). Review and Prospect of Temperature and Humidity Monitoring for Cultural Property Conservation Environments. Journal of Cultural Heritage Conservation, 55, 47–55.
Fiorucci, M., Khoroshiltseva, M., Pontil, M., Traviglia, A., Del Bue, A., and James, S. (2020). Machine Learning for Cultural Heritage: A Survey. Pattern Recognition Letters, 133, 102–108. https://doi.org/10.1016/j.patrec.2020.02.017 DOI: https://doi.org/10.1016/j.patrec.2020.02.017
Furferi, R., Di Angelo, L., Bertini, M., Mazzanti, P., De Vecchis, K., and Biffi, M. (2024). Enhancing Traditional Museum Fruition: Current State and Emerging Tendencies. Heritage Science, 12, 20. https://doi.org/10.1186/s40494-024-01139-y DOI: https://doi.org/10.1186/s40494-024-01139-y
Ivanov, R., and Velkova, V. (2025). Analyzing Visitor Behavior to Enhance Personalized Experiences in Smart Museums: A Systematic Literature Review. Computers, 14, 191. https://doi.org/10.3390/computers14050191 DOI: https://doi.org/10.3390/computers14050191
Jiang, T., Gan, X. E., Liang, Z., and Luo, G. (2022). AIDM: Artificial Intelligence for Digital Museum Autonomous System with Mixed Reality and Software-Driven Data Collection and Analysis. Automated Software Engineering, 29, 22–45. https://doi.org/10.1007/s10515-021-00315-9 DOI: https://doi.org/10.1007/s10515-021-00315-9
Kim, H., and Lee, H. (2022). Emotions and Colors in a Design Archiving System: Applying AI Technology for Museums. Applied Sciences, 12, 1467. https://doi.org/10.3390/app12052467 DOI: https://doi.org/10.3390/app12052467
Münster, S., Maiwald, F., di Lenardo, I., Henriksson, J., Isaac, A., Graf, M. M., Beck, C., and Oomen, J. (2024). Artificial Intelligence for Digital Heritage Innovation: Setting up a RandD Agenda for Europe. Heritage, 7, 794–816. https://doi.org/10.3390/heritage7020038 DOI: https://doi.org/10.3390/heritage7020038
Pietroni, E. (2025). Multisensory Museums, Hybrid Realities, Narration, and Technological Innovation: A Discussion Around New Perspectives in Experience Design and Sense of Authenticity. Heritage, 8, 130. https://doi.org/10.3390/heritage8040130 DOI: https://doi.org/10.3390/heritage8040130
Shi, K., Su, C., and Lu, Y.-B. (2019). Artificial Intelligence (AI): A Necessary Tool for the Future Development of Museums. Science and Technology Museums, 23, 29–41.
Villaespesa, E., and Murphy, O. (2021). This is not an Apple! Benefits and Challenges of Applying Computer Vision to Museum Collections. Museum Management and Curatorship, 36, 362–383. https://doi.org/10.1080/09647775.2021.1873827 DOI: https://doi.org/10.1080/09647775.2021.1873827
Wang, B. (2021). Digital Design of Smart Museum Based on Artificial Intelligence. Mobile Information Systems, 2021, 4894131. https://doi.org/10.1155/2021/4894131 DOI: https://doi.org/10.1155/2021/4894131
Wen, J., and Ma, B. (2024). Enhancing Museum Experience Through Deep Learning and Multimedia Technology. Heliyon, 10, e32706. https://doi.org/10.1016/j.heliyon.2024.e32706 DOI: https://doi.org/10.1016/j.heliyon.2024.e32706
Yang, K., and Wang, H. (2022). The Application of Interactive Humanoid Robots in the History Education of Museums Under Artificial Intelligence. International Journal of Humanoid Robotics, 19, 2250016. https://doi.org/10.1142/S0219843622500165 DOI: https://doi.org/10.1142/S0219843622500165
Zhao, J., and Yezhova, O. (2024). Strategy of Design Online Museum Exhibition Contents from the Perspective of Artificial Intelligence. Art Design, 2, 80–89. https://doi.org/10.30857/2617-0272.2024.2.8 DOI: https://doi.org/10.30857/2617-0272.2024.2.8
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Dr. J. Refonaa, Dr. Satish Upadhyay, Tanya Singh, Divya Sharma, Dr. Nitin Ajabrao Dhawas, Prateek Aggarwal, Dinesh Shravan Datar
This work is licensed under a Creative Commons Attribution 4.0 International License.
With the licence CC-BY, authors retain the copyright, allowing anyone to download, reuse, re-print, modify, distribute, and/or copy their contribution. The work must be properly attributed to its author.
It is not necessary to ask for further permission from the author or journal board.
This journal provides immediate open access to its content on the principle that making research freely available to the public supports a greater global exchange of knowledge.
