Artificial intelligence (AI) addresses complex challenges across climate governance, agriculture, and Earth system management. By integrating large-scale environmental data, AI enables more accurate forecasting, real-time monitoring, and data-driven decision-making. In climate governance, AI supports policymakers by analyzing emissions trends, evaluating policy impacts, and improving transparency in climate commitments. In agriculture, AI-driven tools optimize crop management, enhance resilience to climate change, and reduce resource use through precision farming. At the Earth systems level, AI facilitates deeper insights into processes like land-atmosphere interactions, biodiversity change, and hydrological cycles. Together, these capabilities position AI as an enabler for more adaptive, efficient, and informed approaches to managing environmental systems in the face of climate change. AI for Climate Governance, Agriculture, and Earth Systems explores how AI analyzes environmental data, improves climate modeling, and supports evidence-based decision-making. It examines the potential of AI to enhance sustainability, optimize resource use, and strengthen resilience to climate change while also considering governance, ethical, and policy implications. This book covers topics such as climate change, precision agriculture, and biodiversity, and is a useful resource for engineers, policymakers, academicians, researchers, and earth scientists.