Smart grids are electricity networks as of the new generation who having digital communications for measuring the amount of consumption and the signal to the change at the local level to increase the reliability, efficiency and environmental friendliness of electricity supplying services. Among the functionalities of energy management, supply of electricity is one of the best suited because of the upsurge in the demand, the social and environmental facet and dependability in the supply systems. Energy deal here in the generation, procurement and utilization of electricity and the guideline assist organizations cut costs, be productive, and integrate generation of clean electricity into their operations. Artificial intelligence plays a central role in initiating and determining change of the state on the systems related to energy management of the day, prognosis on failure aspects of the equipment among other improvements in decision-making. Smart sensors and Smart meters may contain the exact data concerning the consumption and demand; thus the AI strategies may be employed to provide the best estimations and identify various types of distortions in order to optimize the utilization of resources. These lead towards the improvement of the energy systems as a capability in offering risks and challenges that can be offered to sustainable development in the future. 2. Overview of Traditional Grids Conventional grids are one in which the electricity is generated from large power stations then transported through high voltage transmission networks and finally to consumers. This structure facilitates the delivery of power but with much problems and difficulties. The current infrastructure becomes inefficient and susceptible to disconnection which puts a lot of challenge to integrate renewable energy and response to the power outages. Moreover, it has been also observed that the conventional ac based electric grid does not possess the capability of monitoring the energy usage and control of energy flow in real time so as to reduce wastage to the maximum possible extent. These limitations have pointed towards the need of modernization that could improve the status of the grid, ensure implementation of the sustainable energy solutions and satisfy the new powering requirements of the modern society. 3. Emergence of Smart Grids It mainly focuses on the concept of using information technology on the existing and typically used electricity transmission and distribution network to create a smarter or advanced grid. Part of the subfields that can be linked to smart grid include smart metering, sensors, communications technologies and smart data processing technologies. In general, these components make it possible to observe the processes, regulate them using feedback loops, and enhance the collection and analysis of data in real time. Key Features and Benefits: - Improved Energy Efficiency: Smart grids play a role in controlling the electricity demand and its COMPLETE eradication. - Integration of Renewable Energy: Most of them support incorporation of other forms of energy such as solar and wind energy. - Enhanced Reliability: Smart grids possess the ability to respond to the issues of outages and demand since they are easily convenient in provision of electrical power. - Cost Savings and Reduced Emissions: For the aspects such as costs and carbon reduction it is a win-win situation for the utility providers as well as the end consumers. Transition from Traditional to Smart Grids: Still, becomes the procedure of increasing quality of the modern construction, the implementation of the new technologies and the stimulation of the cooperation of the subjects. It is very crucial in the development of twenty-first century energy requirement and sustainable development. 4. Role of AI in Smart Grids Data Collection and Analysis: AI improves smart grids through the analysis of big data from smart meters, sensors, and the various parts of the grid. Through this data analysis, the energy distribution and usage is directly monitored and can be improved as decisions are made instantly. Predictive Maintenance: Grid failure and maintenance indices are forecasted by matrices of AI algorithms using historical and real-time data from the grid components. In this way, such a proactive strategy decreases time loss, as well as the usage of resources, and maintenance costs. Demand Response and Load Forecasting: AI enhances demand response and load forecasting due to the precise capability that is provided by the model of the consumers’ behavior. These provide that energy supply and demand are properly coordinated and the system is protected from blackouts. Integration of Renewable Energy Sources: Energy storage is also enhanced as AI helps in optimizers and scheduling of the amounts of renewable energy sources and their forecast. This makes certain that Clean energy is always available to the grid and hence increases the sustainability of the grid. 5. AI Technologies in Smart Grids Machine Learning Algorithms: Artificial intelligence is used for useful work, such as analyzing massive data, where machine learning allows finding these features and predicting something. In smart grids, they are applied for demand profiling and prediction, for detection of any abnormality and even for optimizing the supply of power, thus can play significant role in increasing the reliability of the smart grid. Neural Networks: Hence, within the broad family of machine learning techniques, something known as neural networks is a useful tool because it works exceptionally well with multifaceted, non-linear relationships within the data set in question. Smart grids utilize them in some things like fault detection, load prediction and integration of renewable energy resources. Reinforcement Learning: Reinforcement learning is capable of making the smart grid self-optimizing through the capability of learning from the environment. This technology is used in the dynamic management of energy, in the proper performing of the components of the grid, and in demand response management strategies. IoT Integration and Smart Devices: IoT essentially consists of Smart devices which are essential to smart grids, providing information from different sections of grid. AI in turn uses this data for analytics that facilitates the application of precise control and monitoring over the grid. Smart devices include smart meters and sensors which assists in automating energy usage and engaging the consumer hence improving on the usage of energy. 6. Case Studies and Applications Successful Implementations Worldwide: Therefore, the experiences with the enhancement of the frameworks of today’s grids with the help of technologies that refer to the concept of smart grid have been successfully implemented on the global range. For example, the Pacific Gas and Electric Company of the USA has recently embarked on using smart grid in an attempt to satisfy its customers as well as ensure supply reliability of its customers. For instance, Germany and Denmark has incorporated the use of smart grids in the case of integrating renewable energy and eradicating carbon. The type of implementations elucidated above is adequate for the constructive demonstrations that smart grids are apt to re- envision electricity systems in the global realm. Urban vs. Rural Applications: Smart technology services of the grid also differ in the urban area as well as in the rural area. In the modern cities, smart grid systems are applied to the cluster load control with the restrictions for the connection of dispersed generation and storage equipment, as well as photovoltaic panels. Concerning the country areas, smart grids improve the centralized delivery of electricity and the accomplishment of new electricity sources that are relatively renewable. For instance, Smart grid schemes hand out rural areas of India because they bring cheap and reliable electricity to lift levels of living standards and development. Impact on Energy Efficiency and Sustainability: Most novelties and critical shifts related to smart grids and the effect of such grids on the effectiveness and earth-friendly use of energy. They control power flow, minimize wastage and are involved in the incorporation of REs hence decreasing the use of fossil energy. For instance, tests carried out on Smart City in Japan have pointed out that ITS smart grids would need lower energy and carbon emissions. Further, electric automobiles and energy storage systems in new intelligent networks improve the energy resources system and the structural stability of the automatic system. 7. Benefits of AI-Powered Smart Grids Enhanced Energy Efficiency: In terms of supply chain, they reduce the wastage involved in distribution of energy through the usage of smart grids developed through artificial intelligence. By collecting pertinent data and determining demand tendencies of power, these grids guarantee the effective usage of power thus introducing distinct power saving. Reduced Operational Costs: AI integrated smart grids also result in efficient reduction of operational costs through automation of many features related to grid management. The application of predictive maintenance eliminates most repair cases and helps to increase the shelf life of grid assets. Also, through the application of AI for demand forecasting, resources are well utilized minimizing wastage of resources. Improved Reliability and Stability: Due to AI, smart grids’ reliability and stability are assured because of real-time monitoring and the immediate response to occurrences of abnormalities. More details; predictive analysis can help identify some failures before they occur and work on solving them in advance which may help in the reduction of power failures. This action helps in maintaining stability in the supply of power delivered to the consumer. Environmental Benefits: Smart grids that are powered by artificial intelligence help in managing utilization of renewable energy like the solar and the wind power. Conserving energy and expressing less dependency on most brands of fossil fuels results in less emission of green house gases. Moreover, the minimization of wasted energy and the enhancement of the power infrastructure’s effectiveness reduce greenhouse gas emissions throughout the energy sector. 10. Conclusion Thus, it may be stated that AI-based smart grids are defined as the new development in the field of electricity supply and distribution. The latter adapt consumption, expenses, and stability of power girds with the help of several AI facilities, including ML/DL, NN, IoT, and others. Thus, as the presented numerous successful examples of smart grid integration all over the world including both the urbanized and the non-urbanized areas show, such systems can enhance the energy systems all over the world and contribute to the sustainable development. This means that the further advancement of smart grids based on AI technology is interlinked with the improvement of this process with support of multiple-sided actors in the given field. Advanced, future AI and smart grid technologies will extend higher levels of RE linkages, better demand prediction, and better reliability. Government, service providers and Information technology Oriented companies have to discover the ways to finance smart grids, the policies required for this venture and the people’s perception of smart grids. Hence, there is need to prompt stakeholders to enhance the use of smart grids through the incorporation of AI. Governments should also engage in formulation of friendly and supportive polices that will encourage investment on smart grid. It is for this reason that the further development and invest in smart grid measures is the industry’s responsibility and the interaction with consumers for the intensification of the received benefits. The professionals engaged in the creation of such technologies and researchers should introduce only new innovations into the society and further on, provide solutions to the existing issues occurring in the sphere. Therefore, it will become possible to generate more sufficient, effective and reliable models of energy.