Artificial intelligence (AI) has the potential to revolutionize the power grid in the upcoming years. It will play a crucial role in a move toward smart grids, leading to higher reliability, scalability, and efficiency. Recent years have seen many advancements in the field of machine learning. This has also translated into the paradigm of smart grids as these advancements have led to a significant increase in the prediction accuracy of these algorithms or models. This, in turn, has led to better demand response strategies. In addition to demand response, fault prediction is another field in which AI excels. Due to AI models, faults and maintenance needs can be quickly identified and tended to. This has netted smart grids huge gains in reliability. Moreover, the integration of AI into smart grids also allows the integration of distributed renewable sources of energy. AI can be used for monitoring energy storage, predicting production, and allowing the management of such intermittent sources of energy. In addition to its many advantages for operators and utilities, AI integration into the grid also provides consumers with more insights into their usage and customized energy management solutions. This is expected to lead to wide-scale energy conservation and reduced costs for consumers. While challenges regarding data privacy, security, and interoperability still persist, it is becoming more and more apparent that AI has a huge role to play in the future of smart grids. This chapter aims to thoroughly explore the current and future applications of AI in smart grids and their benefits and drawbacks.