Olatokunbo Demola Salami is a researcher and economist specializing in petroleum and energy economics, with research interests in oil price volatility, government expenditure, economic performance, clean energy, and sustainable development. He is currently pursuing a PhD in Petroleum & Energy Economics at Lagos State University, Nigeria, where his research examines the relationship between oil price volatility, government expenditure, and economic performance in selected Sub-Saharan African countries. He holds an MSc in Economics from Lagos State University and a BSc in Accounting from Ambrose Alli University. He has research experience with Lagos State University, the Institute for Educational Research and Publication (IFERP), India, and PAC Research, Nigeria, contributing to data analysis and sectoral research covering energy, transportation, environment, and investment trends. His expertise includes econometric modeling, time-series and panel-data analysis, forecasting, scenario analysis, cost-benefit analysis, and data visualization. He is an Associate Member of several professional organizations, including the Nigerian Economic Society and the Nigerian Association of Energy Economics.

Artificial Intelligence, Climate Change Mitigation, and Clean Energy Solutions: Pathways to Environmental Sustainability AbstractThis research will be centered on the interface between artificial intelligence and solutions for climate change and clean energy. The importance of artificial intelligence in making clean energy innovations as well as in the efficient utilization of energy will be elaborated in this paper over the period 2000–2025. The ordinary least squares (OLS), unit root tests, and co-integration test, granger causality tests, and autoregressive distributed lag (ARDL) models were used to estimate the short- and long run dynamics of the relationship. The study findings show and demonstrate that artificial intelligence enhances climate change mitigation, improves clean energy efficiency, and promotes environmental sustainability through data-driven innovation, resource optimization, and informed decision-making. On the final note, artificial intelligence is a key driver of climate change mitigation and clean energy adoption, fostering environmental sustainability through innovation, efficient resource management, and supportive policies. Keywords: artificial intelligence, climate change, clean energy, energy efficiency, environmental sustainability, ordinary least square, unit root tests, co-integration test, granger causality tests, and autoregressive distributed lag.