Leveraging Artificial Intelligence for Climate Change Mitigation in Africa: A Sustainable Approach
Abstract
As climate change intensifies environmental and socio-economic vulnerabilities across Africa, there is a growing need for innovative, scalable solutions to support climate resilience. This study critically examines the role of Artificial Intelligence (AI) in enhancing climate adaptation and mitigation efforts on the continent. Employing a qualitative, multi-source research methodology, the paper synthesizes academic literature, institutional frameworks, and applied case studies to assess the integration of AI into environmental monitoring and resource management systems. Particular emphasis is placed on the use of machine learning and remote sensing technologies to support real-time data analysis, land-use classification, water resource management, and early warning systems. The Enhancing National Climate Services (ENACTS) program is analyzed as a leading case, demonstrating how the fusion of satellite and ground- based data can significantly improve climate services in sectors such as agriculture and public health. The paper also identifies critical challenges—including data scarcity, inadequate infrastructure, limited technical capacity, and ethical risks such as data privacy and algorithmic bias—that hinder the effective deployment of AI. In response, the study offers strategic policy recommendations to strengthen climate data infrastructure, promote cross-sector collaboration, and build human capital in AI and climate science. The findings underscore the importance of African-led innovation, ethical governance, and context-specific solutions in ensuring that AI contributes meaningfully and equitably to sustainable development and climate resilience.
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