The growing increase in the global demand for energy across industries have led to higher emissions of greenhouse gases (GHG) into the earth’s atmosphere. Manufacturing factories, power plants and the vast transportation industry all use the energy derived from fossil fuels. Unfortunately, the adverse effect of the release of these gases is seen in its impact on climate change. This reality has made it important to examine strategies for addressing the impact of climate change. States and corporate bodies are now beginning to consider strategies for addressing their climate footprints. As such, various industries whose use of energy from fossil fuels impact the environment are devising means of reducing their GHG emissions. One effective method that is gaining traction within the energy sector is the Carbon Capture Utilization and Storage (CCUS). This process broadly involves the use of techniques to contain Carbon dioxide (CO₂) emissions by capturing and conveying it from its point of release for either processing, storage or permanent disposal. This process decreases the release of carbon into the atmosphere. Over the last couple of years, there is an emerging consensus that this method is important in reaching Net Zero and in the energy industry, there is growing momentum on participation in these Low Carbon Solutions (LCS) in order to reduce the impact of these emissions on the environment and on the climate. However, as the CCUS technology involves injecting carbon dioxide underground through drilled wells, it is important that these technologies are built properly and that they are continuously efficient. In this article, I argue that the onset of artificial intelligence (AI) presents an opportunity to build intelligent underground wells for CCUS. However, there are some key areas which policy makers need to pay attention to with the use of AI in this process. In this article, I explain what this entails.

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