The integration of artificial intelligence (AI) into liposome engineering represents a groundbreaking advancement in the field of targeted drug delivery, particularly for marine bioactive peptides. Liposomes, as versatile drug carriers, offer numerous benefits, including enhanced bioavailability, reduced toxicity, and the ability to encapsulate both hydrophilic and hydrophobic drugs. Marine b ioactive peptides, with their unique therapeutic properties, hold significant potential in pharmaceutical applications. However, the challenge lies in optimizing liposome formulations for efficient and targeted delivery of these peptides. AI driven approac hes address this challenge by leveraging advanced machine learning algorithms to analyze vast datasets, predict liposome behavior, and optimize formulations. In this review, we explore the synergy between AI and liposome technology, focusing on the methods and types of liposome preparation, such as thin film hydration and ethanol injection, and their functionalization for targeted delivery through strategies like PEGylation and ligand attachment. We discuss the application of AI models, including neural net works and decision trees, in predicting liposome stability, optimizing formulation parameters, and designing experiments. Additionally, we highlight the current pharmacological applications of marine bioactive peptides and present case studies demonstratin g their successful integration into AI optimized liposome systems. Despite the significant advancements, challenges remain in data availability, model scalability, and reproducibility. Future directions emphasize the need for continuous improvement in AI t echniques, integration with multi omics data, and the development of smart liposomes capable of stimuli responsive drug release. Ethical and regulatory considerations are also addressed to ensure safe and equitable application of these technologies. AI dri ven liposome engineering offers a promising pathway to enhance the delivery and efficacy of marine bioactive peptides, paving the way for innovative therapeutics in personalized medicine. Further research and interdisciplinary collaboration will be crucial in overcoming current limitations and realizing the full potential of this transformative approach.