This article investigates the integration of artificial intelligence (AI) with smart grid technology to boost energy management, forecasting accuracy, and overall efficiency. Smart grids, as modernized digital energy distribution networks, employ AI to optimize the flow of electricity, predict energy consumption, and integrate renewable energy sources. Through a comprehensive analysis of current literature, the paper emphasizes major AI technologies, such as machine learning, deep learning, and reinforcement learning, and their applicability in smart grid operations. The article also addresses the benefits AI delivers, such as boosting energy efficiency, decreasing costs, and enhancing grid stability, while also addressing the limitations and obstacles that accompany its deployment, such as data privacy concerns and technology integration issues. By addressing gaps in present research, the article stresses AI’s transformative potential for delivering sustainable and adaptive energy solutions. The findings show that additional developments in AI can lead to considerable improvements in smart grid performance, enabling a more efficient and robust energy infrastructure.