This review explores the integration of artificial intelligence (AI) in drone control, highlighting its impact on enhancing drone autonomy and performance across various applications. The study examines the latest developments and applications of AI in drone operations, including cargo transportation, agriculture, construction, security, and disaster response. AI has significantly improved the autonomy of drones, enabling them to perform complex tasks without direct human supervision. The paper discusses the use of AI algorithms such as deep learning (DL), machine learning (ML), and reinforcement learning (RL) in optimizing drone operations, including navigation, object recognition, and decision-making. It also addresses the ethical and regulatory challenges associated with AI in drone technology. The review covers the development of autonomous navigation systems, predictive maintenance, and the use of AI in logistics and supply chain management. The study emphasizes the importance of AI in improving the efficiency and sustainability of drone-based operations, while also highlighting the need for further research in this field. The paper provides a comprehensive overview of the current state of AI applications in drones, including the use of meta-heuristic algorithms, collaborative communication between drones, and the integration of AI with cloud-based systems for training and simulation. The review also discusses the technical aspects of drones, such as their morphology, flight time, payload capacity, range, and battery technology. The study concludes that AI has the potential to revolutionize drone technology, enabling more efficient and effective operations in various industries. The paper highlights the importance of continued research and development in AI applications for drones to address the challenges and opportunities in this rapidly evolving field.This review explores the integration of artificial intelligence (AI) in drone control, highlighting its impact on enhancing drone autonomy and performance across various applications. The study examines the latest developments and applications of AI in drone operations, including cargo transportation, agriculture, construction, security, and disaster response. AI has significantly improved the autonomy of drones, enabling them to perform complex tasks without direct human supervision. The paper discusses the use of AI algorithms such as deep learning (DL), machine learning (ML), and reinforcement learning (RL) in optimizing drone operations, including navigation, object recognition, and decision-making. It also addresses the ethical and regulatory challenges associated with AI in drone technology. The review covers the development of autonomous navigation systems, predictive maintenance, and the use of AI in logistics and supply chain management. The study emphasizes the importance of AI in improving the efficiency and sustainability of drone-based operations, while also highlighting the need for further research in this field. The paper provides a comprehensive overview of the current state of AI applications in drones, including the use of meta-heuristic algorithms, collaborative communication between drones, and the integration of AI with cloud-based systems for training and simulation. The review also discusses the technical aspects of drones, such as their morphology, flight time, payload capacity, range, and battery technology. The study concludes that AI has the potential to revolutionize drone technology, enabling more efficient and effective operations in various industries. The paper highlights the importance of continued research and development in AI applications for drones to address the challenges and opportunities in this rapidly evolving field.