MANAGEMENT PERSPECTIVES ON AI-POWERED SCULPTURE GALLERIES
DOI:
https://doi.org/10.29121/shodhkosh.v6.i1s.2025.6634Keywords:
Artificial Intelligence, Sculpture Galleries, Management Perspectives, Art Curation, Digital TransformationAbstract [English]
The convergence of artificial intelligence (AI) and art has been significant in the way the sculpture show is presented in contemporary sculpture, how it is managed and experienced by people. The study will look at the sentiments of management regarding the implementation of AI powered art shows with a specific interest on how this may impact on the management strategies, tactical and marketing impacts. The new artificial intelligence technologies of smart gallery selection, predictive maintenance, data-driven decision-making, and personalised guest experience have changed the traditional gallery management. AI allows managers to deal with innovation easier and plan strategically. It also assists them in choices between fantasy and technological effectiveness. Introducing AI into the field of sculpting galleries has improved the way resources are used and how the costs are matched against the benefits as well. This allows galleries to continue producing excellent art and make money. AI-driven automation changes the way work get done by making it easier for curators to organise digital files and look at guest data to find ways to connect them more effectively. AI analytics are being used more and more by managers to divide audiences into groups, predict trends and make the most of show plans. Also, the role of AI in virtual and augmented reality is changing the way people interact with art so that it is easier for more people around the world to see it. But these new ideas come with problems, such as limited funds, poor technology and people who don't like change among traditional partners. Concerns about sincerity and the artist's part, come from an ethical and artistic point of view making it more difficult for managers to make decisions.
References
Avlonitou, C., and Papadaki, E. (2025). AI: An Active and Innovative Tool for Artistic Creation. Arts, 14(3), Article 52. https://doi.org/10.3390/arts14030052 DOI: https://doi.org/10.3390/arts14030052
Cao, Y., Li, S., Liu, Y., Yan, Z., Dai, Y., Yu, P. S., and Sun, L. (2023). A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT (arXiv Preprint No. 2303.04226). arXiv. https://doi.org/10.48550/arXiv.2303.04226
Cetinic, E., and She, J. (2021). Understanding and Creating art With AI: Review and Outlook. ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), 18, 1–22. https://doi.org/10.1145/3475799 DOI: https://doi.org/10.1145/3475799
Huang, M.-H., and Rust, R. T. (2020). A Strategic Framework for Artificial Intelligence in Marketing. Journal of the Academy of Marketing Science, 49, 30–50. https://doi.org/10.1007/s11747-020-00749-9 DOI: https://doi.org/10.1007/s11747-020-00749-9
Huang, P.-C., Li, I.-C., Wang, C.-Y., Shih, C.-H., Srinivaas, M., Yang, W.-T., Kao, C.-F., and Su, T.-J. (2025). Integration of Artificial Intelligence in Art Preservation and Exhibition Spaces. Applied Sciences, 15(2), Article 562. https://doi.org/10.3390/app15020562 DOI: https://doi.org/10.3390/app15020562
Kiourexidou, M., and Stamou, S. (2025). Interactive Heritage: The Role of Artificial Intelligence in Digital Museums. Electronics, 14(9), Article 1884. https://doi.org/10.3390/electronics14091884 DOI: https://doi.org/10.3390/electronics14091884
Longo, M. C., and Faraci, R. (2023). Next-Generation Museum: A Metaverse Journey into the Culture. Sinergie Italian Journal of Management, 41, 147–176. https://doi.org/10.7433/s120.2023.08 DOI: https://doi.org/10.7433/s120.2023.08
Mossavar-Rahmani, F., and Zohuri, B. (2024). ChatGPT and Beyond the Next Generation of AI Evolution (A communication). Journal of Energy and Power Engineering, 18, 146–154. https://doi.org/10.17265/1934-8975/2024.04.003 DOI: https://doi.org/10.17265/1934-8975/2024.04.003
Oksanen, A., Cvetkovic, A., Akin, N., Latikka, R., Bergdahl, J., Chen, Y., and Savela, N. (2023). Artificial Intelligence in Fine Arts: A Systematic Review of Empirical Research. Computers in Human Behavior: Artificial Humans, 1, Article 100004. https://doi.org/10.1016/j.chbah.2023.100004 DOI: https://doi.org/10.1016/j.chbah.2023.100004
Padigel, C., Koli, K., Tiple, S., and Suryawanshi, Y. (2025). Detection, Monitoring and Follow-Up of ADHD Suffering Children using Deep Learning. International Journal of Electrical Engineering and Computer Science (IJEECS), 14(1), 204–210.
Rani, S., Dong, J., Dhaneshwar, S., Siyanda, X., and Prabhat, R. S. (2023). Exploring the Potential of Artificial Intelligence and Computing Technologies in art Museums. ITM Web of Conferences, 53, Article 01004. https://doi.org/10.1051/itmconf/20235301004 DOI: https://doi.org/10.1051/itmconf/20235301004
Singh, A., Kanaujia, A., Singh, V. K., and Vinuesa, R. (2023). Artificial Intelligence for Sustainable Development Goals: Bibliometric Patterns and Concept Evolution Trajectories. Sustainable Development, 32, 724–754. https://doi.org/10.1002/sd.2706 DOI: https://doi.org/10.1002/sd.2706
Siri, A. (2024). Emerging Trends and Future Directions in Artificial Intelligence for Museums: A Comprehensive Bibliometric Analysis based on Scopus (1983–2024). Geopolitical, Social Security and Freedom Journal, 7(1), 20–38. https://doi.org/10.2478/gssfj-2024-0002 DOI: https://doi.org/10.2478/gssfj-2024-0002
Tang, X., Zhang, P., Du, J., and Xu, Z. (2021). Painting and Calligraphy Identification Method Based on Hyperspectral Imaging and Convolution Neural Network. Spectroscopy Letters, 54(9), 645–664. https://doi.org/10.1080/00387010.2021.1982988 DOI: https://doi.org/10.1080/00387010.2021.1982988
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(4), 362–383. https://doi.org/10.1080/09647775.2021.1873827 DOI: https://doi.org/10.1080/09647775.2021.1873827
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Dr. Yukti Khajanchi, Dr. S.Prayla Shyry, Ramesh Saini, Khushboo, Sidhant Das, Mr. Barathnivash. V

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.























