Artificial intelligence (AI) is revolutionizing pharmaceutical sciences by transforming drug discovery, development, and clinical applications. This chapter explores the origins, principles, and applications of AI in pharmaceutical sciences, emphasizing its role in overcoming long-standing challenges such as lengthy timelines, high costs, and low success rates. AI technologies, including machine learning (ML) and deep learning (DL), enable data-driven insights, predictive modeling, and automation across the drug development pipeline. Key applications include target identification, lead optimization, ADMET profiling, clinical trial design, and personalized medicine. The chapter also highlights the integration of AI with robotics for high-throughput experimentation and the use of generative models for de novo drug design. Ethical considerations, challenges like model interpretability, and future trends such as explainable AI (XAI) and federated learning are discussed. AI's transformative potential in pharmaceutical sciences promises faster, cost-effective, and precise drug development while addressing critical challenges in healthcare.