The integration of Artificial Intelligence (AI) into drone technology has significantly advanced the capabilities of drones, particularly in areas such as logistics, agriculture, and security. This study examines the impact of AI on improving drone autonomous behavior, from automation to complex real-time decision-making. The paper provides detailed examples of the latest developments and applications, including advanced algorithms for object detection, trajectory optimization, and collaborative communication between drones. Ethical and regulatory challenges are also discussed, highlighting the potential socioeconomic impact of AI-driven drones. The introduction of AI has revolutionized various industrial sectors, enhancing performance and efficiency. Drones are now used for cargo transportation, logistics optimization, and environmental monitoring, among other applications. AI algorithms, such as Deep Learning (DL), have enabled drones to make complex decisions in real-time, improving their adaptability and reliability. However, the integration of AI in drones also raises ethical and regulatory concerns, particularly regarding the balance between autonomy and human supervision. The paper's methodology involves a structured search and analysis of relevant scientific articles, focusing on publications after 2019. The background section covers the theoretical foundations of AI, including supervised learning, unsupervised learning, reinforcement learning, and meta-heuristic algorithms. These techniques are applied to various drone operations, such as cargo transport, logistics optimization, and agricultural tasks. The state-of-the-art section reviews promising research areas where AI algorithms have made significant contributions. It discusses challenges in cargo delivery, including efficient battery management, external factors like weather conditions, and airspace regulations. The paper also explores adaptive models, dynamic delivery optimization, and collaborative routing strategies. Additionally, it highlights the importance of AI in last-mile delivery, urban and catastrophic area deliveries, and agricultural operations. Overall, the integration of AI in drones has led to notable progress in autonomy and efficiency, but it also demands careful consideration of ethical and regulatory issues to ensure responsible and sustainable development.The integration of Artificial Intelligence (AI) into drone technology has significantly advanced the capabilities of drones, particularly in areas such as logistics, agriculture, and security. This study examines the impact of AI on improving drone autonomous behavior, from automation to complex real-time decision-making. The paper provides detailed examples of the latest developments and applications, including advanced algorithms for object detection, trajectory optimization, and collaborative communication between drones. Ethical and regulatory challenges are also discussed, highlighting the potential socioeconomic impact of AI-driven drones. The introduction of AI has revolutionized various industrial sectors, enhancing performance and efficiency. Drones are now used for cargo transportation, logistics optimization, and environmental monitoring, among other applications. AI algorithms, such as Deep Learning (DL), have enabled drones to make complex decisions in real-time, improving their adaptability and reliability. However, the integration of AI in drones also raises ethical and regulatory concerns, particularly regarding the balance between autonomy and human supervision. The paper's methodology involves a structured search and analysis of relevant scientific articles, focusing on publications after 2019. The background section covers the theoretical foundations of AI, including supervised learning, unsupervised learning, reinforcement learning, and meta-heuristic algorithms. These techniques are applied to various drone operations, such as cargo transport, logistics optimization, and agricultural tasks. The state-of-the-art section reviews promising research areas where AI algorithms have made significant contributions. It discusses challenges in cargo delivery, including efficient battery management, external factors like weather conditions, and airspace regulations. The paper also explores adaptive models, dynamic delivery optimization, and collaborative routing strategies. Additionally, it highlights the importance of AI in last-mile delivery, urban and catastrophic area deliveries, and agricultural operations. Overall, the integration of AI in drones has led to notable progress in autonomy and efficiency, but it also demands careful consideration of ethical and regulatory issues to ensure responsible and sustainable development.