Artificial intelligence (AI) has emerged as a transformative tool in pharmacology and pharmaceutics, enabling accelerated drug discovery, formulation optimization, and clinical translation. Machine learning, deep learning, and predictive modeling improve target identification, lead optimization, and personalized therapy. AI-driven platforms facilitate high-throughput screening, pharmacokinetic/pharmacodynamic (PK/PD) modeling, and nanocarrier design, reducing time, cost, and attrition rates. This review highlights the applications of AI across the drug development pipeline, from molecular discovery to regulatory submission, and discusses challenges, ethical considerations, and future perspectives in precision pharmacotherapy.