Artificial intelligence (AI) has emerged as a pivotal research area with the potential to enable machines to learn and think similarly to human beings. Its advancements have significantly enhanced various sectors, including image classification, speech recognition, and autonomous vehicles. This paper provides a comprehensive review of AI techniques and their applications in resilient and intelligent microgrid control within smart cities. The integration of AI in microgrid control aligns seamlessly with the broader vision of smart cities, ensuring sustainable and resilient energy delivery. The review covers machine learning methods, evolutionary algorithms, fuzzy logic controllers, and more, discussing their contributions and limitations.