Climate change, characterized by long-term shifts in climatic variables such as temperature, rainfall, and wind patterns, profoundly impacts agriculture by affecting crops, soils, livestock, and pests. The rise in global temperatures and CO2 levels, along with changes in precipitation and soil salinity, presents substantial challenges to agricultural productivity. These climatic shifts are expected to decrease crop yields, particularly for staple crops like wheat and rice, while also exacerbating land degradation, soil fertility loss, and desertification. With global food demand projected to increase by 50–54% by 2050, the need for resilient agricultural practices to ensure food security is more urgent than ever. Artificial intelligence (AI) offers promising solutions to these challenges by enhancing precision farming, resource management, and crop monitoring through the integration of remote sensing and simulation models. By leveraging AI-driven insights, agriculture can better adapt to and mitigate the impacts of climate change, supporting sustainable food production amid evolving environmental conditions.