As the drug supply chain becomes more complex and the demand for efficiency and sustainability increases, there is a growing need for innovative approaches in supply chain management. These challenges were required to be dealt with efficiently, and Artificial Intelligence (AI) is definitely a booming technology to meet these challenges through capabilities such as real-time tracking of new drivers, risk management, and notional operational optimization. Using Systematic Literature Review (SLR) method this research synthesizes the content of multiple articles published from 2003 to 2025,with a total of 542 articles and 329 articles. It has a particular focus on AI in Sustainable Supply Chain, discussing factors like predictive analytics, automation, and optimization. Analysis was conducted via a bibliometrics tool (biblioshiny) to uncover the data pertinent literature and trends, assuring all necessary data were included. Results revealed that AI led to a 25% decrease in inventory errors and a growth in forecast accuracy of 40%, resulting in reduced carbon footprints through improved logistics. Moreover, AI-based models showed their ability to overcome fragmented data integration and minimize the risk of drug shortages. These results are highly advantageous for the pharmaceuticals, offering cost savings, faster drug development times, and a stronger focus on sustainability. Also, this study lay a foundation toward knowledge creation on AI use in supply chains and a theoretical stimulating base for future investigations to develop sustainable, integrated, and resilient supply chain systems.