The presented article delves into Artificial Intelligence (AI) and Machine Learning (ML)-assisted approaches for energy management in smart grid operations by considering renewable energy integration. The paper categorizes AI/ML applications into two main areas: demand-side management and supply-side management of smart grids. By synthesizing findings from more than 150 articles and real-world implementations of smart grids, this work underscores the significant impact and various approaches of AI/ML in improving grid resilience and operation. This contribution is crucial, as smart grids represent the future of the power system, and it is important to understand the available solutions for smooth and efficient smart grid operations in smart/future cities. As a result, the work provides a comparative overview of various techniques used for energy management in smart grids, including challenges and scalability considerations. In summary, AI/ML techniques play a key role in smart grid operations. However, it is recommended to develop a validated framework to facilitate decision-making and determine where and how to effectively apply these techniques.