Nano-based drug delivery systems have demonstrated the ability to address challenges posed by therapeutic agents, enhancing drug efficiency and reducing side effects. Various nanoparticles are utilized as drug delivery systems with unique characteristics, leading to diverse applications across different diseases. However, the complexity, cost, and time-consuming nature of laboratory processes, the large volume of data, and the challenges in data analysis have prompted the integration of artificial intelligence (AI) tools. AI has been employed in designing, characterizing, and manufacturing drug delivery nanosystems, as well as in predicting treatment efficiency. AI's potential to personalize drug delivery based on individual patient factors, optimize formulation design, and predict drug properties has been highlighted. By leveraging AI and large datasets, developing safe and effective drug delivery systems can be accelerated, ultimately improving patient outcomes and advancing pharmaceutical sciences. This review article investigates the role of AI in the development of nano-drug delivery systems, with a focus on their therapeutic applications. The use of AI in drug delivery systems has the potential to revolutionize treatment optimization and improve patient care.