Gone are the days when the transition to green energy was an alternative; nowadays, it is a must against climate change. Nonetheless, the incorporation of renewable energy sources (RES) such as wind, solar, hydro, and biomass into the existing power networks of traditional grids is a major problem due to their sporadic and unpredictable nature. Smart grids, however, which are supported by Artificial Intelligence (AI) and the Internet of Things (IoT), do solve the problems and ensure the system is stable, efficient, and sustainable in terms of energy. The use of AI in predicting energy usage and in allocating resources advances the energy grid. IoT devices with sensors send live data, which is used in the decision-making process. Furthermore, developments such as Virtual Power Plants (VPPs), energy storage systems that AI powers, and the use of blockchain to create decentralized energy trading could be considered as additional innovations that allow for the creation of a resilient and smart energy infrastructure. Despite these problems, like attacks on cybersecurity, privacy of personal data, and standardization of IT equipment for data exchange, are the ones that need tackling first. AI automation in the grid, which is enabled by the creation of energy storage solutions, besides coherent policy frameworks, is the main element required for making the shift to renewable energy a seamless process. In addition to the strategies already in place, quantum computing, federated learning, and self-healing grids may be used to make energy efficiency and sustainability reach new heights. The role of AI and IoT in smart grids is studied in this chapter, which points out how they add to the optimization of renewable energy integration, grid stability, and demand-side management, and thus people could live in a world where they can get power in a sustainable, reliable, and efficient way.