AI FOR SUSTAINABLE ART PRODUCTION MANAGEMENT

Authors

  • Abhinav Mishra Chitkara Centre for Research and Development, Chitkara University, Himachal Pradesh, Solan, 174103, India
  • Shriya Mahajan Centre of Research Impact and Outcome, Chitkara University, Rajpura- 140417, Punjab, India
  • Dr. Kunal Meher Assistant Professor, UGDX School of Technology, ATLAS Skill Tech University, Mumbai, Maharashtra, India
  • Dr. Badri Narayan Sahu Professor, Department of Electronics and Communication Engineering, Institute of Technical Education and Research, Siksha 'O' Anusandhan (Deemed to be University) Bhubaneswar, Odisha, India
  • Dr. Sarika Agarwal Associate Professor, Department of Computer Science & Engineering(AI), Noida Institute of Engineering and Technology, Greater Noida, Uttar Pradesh, India
  • Richa Srivastava Assistant Professor, School of Business Management, Noida international University, Noida, Uttar Pradesh, India

DOI:

https://doi.org/10.29121/shodhkosh.v6.i1s.2025.6671

Keywords:

Artificial Intelligence, Sustainable Art Production, Resource Optimization, Generative Design, Environmental Efficiency

Abstract [English]

This study looks into how AI technologies can help artists to use resources more efficiently and make less waste, and make their work more eco-friendly. AI provides tools that enable not only greater creativity but also less damage that can be done to the environment by making and sharing art via AI. It does this by linking new ideas in art with environmental-friendly ways of making things. The first part of the study is an extensive review of the existing literature on the uses of AI in art and acceptance of environmentally friendly methods in creative areas such as design, digital medium, and the visual arts. A mixed approach is applied for the technique, which examines both qualitative and numeric aspects of sustainability, such as energy economy, lifetime effect of materials, and reducing carbon emissions via AI-driven actions. Some important areas of focus are optimising resources with the help of AI, making things that use less energy, and choosing smart materials according to lifecycle analysis. The paper also contains case-studies of digital art platforms that deploy AI, fashion efforts that are good for the environment, and creative AI projects that attempt to reduce waste. The results shows the potential of AI as a creative partner to be a sustainability driver. It can promote responsible innovation without compromising on art purism. The paper comes to the conclusion that the use of AI as a means to aid in making art production more sustainable is a good way for the creative economy to move towards circularity and environmental awareness.

References

Avlonitou, C., and Papadaki, E. (2025). AI: An Active and Innovative Tool for Artistic Creation. Arts, 14, Article 52. https://doi.org/10.3390/arts14030052 DOI: https://doi.org/10.3390/arts14030052

Cai, P., Zhang, K., and Pan, Y. (2023). Application of AI Interactive Device Based on Database Management System in Multidimensional Design of Museum Exhibition Content (Research Square Preprint). https://doi.org/10.21203/rs.3.rs-3074947/v1 DOI: https://doi.org/10.21203/rs.3.rs-3074947/v1

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).

Chang, L. (2021). Review and Prospect of Temperature and Humidity Monitoring for Cultural Property Conservation Environments. Journal of Cultural Heritage Conservation, 55, 47–55

Gaber, J. A., Youssef, S. M., and Fathalla, K. M. (2023). The Role of Artificial Intelligence and Machine Learning in Preserving Cultural Heritage and art Works via Virtual Restoration. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 10, 185–190. https://doi.org/10.5194/isprs-annals-X-1-W1-2023-185-2023 DOI: https://doi.org/10.5194/isprs-annals-X-1-W1-2023-185-2023

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, Article 562. https://doi.org/10.3390/app15020562 DOI: https://doi.org/10.3390/app15020562

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

Qin, Y., Xu, Z., Wang, X., and Skare, M. (2023). Artificial Intelligence and Economic Development: An Evolutionary Investigation and Systematic Review. Journal of the Knowledge Economy, 15, 1736–1770. https://doi.org/10.1007/s13132-023-01183-2 DOI: https://doi.org/10.1007/s13132-023-01183-2

Sha, Y., Zhang, S., Feng, T., and Yang, T. (2021). Research on the Intelligent Display of Cultural Relics in Smart Museums Based on Intelligently Optimized Digital Images. Computational Intelligence and Neuroscience, 2021, Article 7077556. https://doi.org/10.1155/2021/7077556 DOI: https://doi.org/10.1155/2021/7077556

Shambharkar, S., Thakare, K., Takkamore, S., Padole, R., and Chaure, K. (2025). Detection of DDoS Attack in Cloud Computing Using Machine Learning Algorithm. International Journal of Electrical Engineering and Computer Science (IJEECS), 14(1), 239–242 .

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, 20–38. https://doi.org/10.2478/gssfj-2024-0002 DOI: https://doi.org/10.2478/gssfj-2024-0002

Wang, B. (2021). Digital Design of Smart Museum Based on Artificial Intelligence. Mobile Information Systems, 2021, Article 4894131, 1–13. https://doi.org/10.1155/2021/4894131 DOI: https://doi.org/10.1155/2021/4894131

Zhao, J., and Yezhova, O. (2024). Strategy of Design Online Museum Exhibition Contents from the Perspective of Artificial Intelligence. Art and Design, 8, 80–89. https://doi.org/10.30857/2617-0272.2024.2.8 DOI: https://doi.org/10.30857/2617-0272.2024.2.8

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Published

2025-12-10

How to Cite

Mishra, A., Mahajan, S., Meher, K., Sahu, B. N., Agarwal, S., & Srivastava, R. (2025). AI FOR SUSTAINABLE ART PRODUCTION MANAGEMENT. ShodhKosh: Journal of Visual and Performing Arts, 6(1s), 318–327. https://doi.org/10.29121/shodhkosh.v6.i1s.2025.6671