Balancing AI Growth with Environmental Sustainability: Future Challenges & Innovations

Jyoti Singh Vishaka Sonkar, Mohd Asad Ali Khan

Authors

Jyoti Singh Vishaka Sonkar, Mohd Asad Ali Khan

Abstract

Artificial Intelligence (AI) is reshaping economies, industries, and daily life. However, its rapid expansion comes with rising energy consumption, increased carbon footprints, and resource demands. This paper explores the environmental challenges posed by AI growth, evaluates current mitigation strategies, and outlines future innovations that can align AI development with ecological sustainability. The goal is to map pathways for responsible AI that supports both technological progress and planetary health.

References

Agarwal, C., & Rai, P. (2025, October 15). Environmental wisdom and sustainable practices. In Bridging ideas: A multidisciplinary approach to knowledge and innovation (pp. 76–85). Eagle Leap Printers and Publishers Pvt. Ltd.

Bauer, S., & Lefevre, A. (2023). AI and energy consumption: Challenges and opportunities. Journal of Sustainable Computing, 18(2), 112–129.

Dubey, V., Kumari, P., Singh, O. P., & Mishra, G. R. (2023). 17 Wearable Technology. Concepts of Artificial Intelligence and its Application

Dubey, V., Singh, S., Kumari, P., Patel, K., Jahan, T., & Dubey, S. (2026). AI-Driven Business Systems: Pioneering Innovation and Transformation. In Integrating AI and Machine Learning into Business and Management Education (pp. 297-332). IGI Global Scientific Publishing.

Hasan, N., Agarwal, C., Joshi, A., Rahal, D., Traisa, R., & Sharma, S. (2025). The two-way influence of green banking practices and green electronic word of mouth in driving green trust and green loyalty: A trust transfer perspective. International Journal of Ethics and Systems. Advance online publication. https://doi.org/10.1108/IJOES-10-2024-0326

Henderson, P., et al. (2020). Efficient processing of deep neural networks: A survey of hardware and algorithms. IEEE Transactions on Neural Networks and Learning Systems, 31(8), 2711–2733.

Shrivastava, S., Khalid, S., & Nishad, D. K. (2024). Impact of EV interfacing on peak-shelving and frequency regulation in a microgrid. Scientific Reports, 14(1), 31514.

Strubell, E., Ganesh, A., & McCallum, A. (2019). Energy and policy considerations for deep learning in NLP. Proceedings of the AAAI Conference on Artificial Intelligence, 33(1), 13693–13696.

Tripathi, K., Shrivastava, S., & Banarjee, S. (2020). Review in Recent Trends on Energy Delivery System and Its Issues in Smart Grid System. Computing Algorithms with Applications in Engineering: Proceedings of ICCAEEE 2019, 117-125.

United Nations Environment Programme. (2024). Global E-waste Monitor 2024. UNEP Publications.

Wadhawan, D. N. (2025). Harnessing artificial intelligence in healthcare management: A study with respect to prospects and obstacles. In Proceedings of the International Conference on Next Generation Information System (ICNGIS 25)

Zeng, Y., et al. (2022). AI for climate change adaptation and mitigation: A review. Environmental Research Letters, 17(10), 103001.