A Review of Artificial Intelligence Applications in Climate Change Mitigation

Sandiponi Tasha *

Department of Extension Education and Communication Management, Faculty of Community Science, Assam Agricultural University, Jorhat-785013, Assam, India.

*Author to whom correspondence should be addressed.


Abstract

The World Meteorological Organisation defines climate as long-term weather patterns observed over decades or centuries, and these patterns have changed dramatically in recent years, mainly because of human activities like burning fossil fuels and cutting down forests. Artificial Intelligence (AI) has emerged as a transformative technology capable of addressing climate-related challenges across various sectors. This review explored the intersection of AI and climate change mitigation, highlighting how AI technologies such as machine learning, deep learning, natural language processing, and remote sensing contribute to monitoring emissions, forecasting weather, optimising energy systems, and supporting sustainable agriculture. The paper also discussed AI’s role in disaster risk management by enabling rapid data analysis and decision-making during emergencies. The findings revealed that AI's value in addressing climate change comes from its capacity to monitor environmental factors, forecast future conditions, and optimise resource use. Despite its immense potential, the deployment of AI in climate action faces several challenges, including high energy consumption, data scarcity, ethical concerns, and infrastructure limitations, particularly in under-resourced regions. Nevertheless, advancements in energy-efficient AI models, integration with IoT and satellite systems, and developments in decentralised learning techniques present significant opportunities for the future. This paper concluded that while AI is not a standalone solution, it is a critical component in the global climate mitigation strategy. With the right investments in education and research, AI has the potential to become a cornerstone of global climate action. Again, responsible implementation and cross-sector collaboration, AI can accelerate progress toward a more sustainable and climate-resilient future.

Keywords: Artificial intelligence, climate change mitigation, machine learning, renewable energy, sustainable agriculture


How to Cite

Tasha, Sandiponi. 2025. “A Review of Artificial Intelligence Applications in Climate Change Mitigation”. International Journal of Environment and Climate Change 15 (5):443-49. https://doi.org/10.9734/ijecc/2025/v15i54864.

Downloads

Download data is not yet available.