Harnessing artificial intelligence to mitigate CO2 emissions and optimize energy use in Sub-saharan africa: Implications for sustainable economic growth

This research aims to investigate the potential of artificial intelligence (AI) applications in addressing the energy consumption and CO2 emissions challenges faced by countries in Sub-Saharan Africa (SSA) and their implications for economic growth. It employed a theoretical approach towards examining how AI mitigates CO2 emissions and optimizes energy use in SSA countries. It identified opportunities for AI integration to enhance energy efficiency, while reducing carbon footprints, and promoting sustainable economic development. The findings were observed through a comprehensive analysis of systematic reviews, and desk reviews of documents on energy use in SSA countries. Some of the findings revealed that technologies such as machine learning (ML) algorithms analyse real-time data to predict energy demands, leading to more efficient usage and reduced waste in SSA countries. This efficiency is crucial in industries like manufacturing, where AI optimizes production processes, thereby lowering energy consumption and associated carbon emissions. It is imperative for policy makers in this region to prioritize AI sources in order to efficiently harness energy use in the SSA Countries.