Pharmaceutics and drug delivery are entering the mainstream orbit of the pharmaceutical industry due to the dramatically increasing cost of developing new molecular entities (NMEs). Current pharmaceutical product development still traditionally depends on trial-and-error approaches by personal experience. However, recent pharmaceutical researches show that significantly evolved artificial intelligence (AI) and machine learning techniques are promising to facilitate the drug delivery system development. AI can process big data, reveal potential correlations, provide accurate predictions, and navigate in a high-dimensional space, offering great potential to change the drug delivery research paradigm. Data-driven approaches can be applied to all aspects of the pharmaceutical field, across preformulation studies, formulation screening, and precision medicine in the clinic. AI especially benefits the development of advanced drug delivery systems, such as nanoparticles and protein drugs, due to the complexity of these innovative dosage forms. In this chapter, we provide a comprehensive and detailed review of all aspects of AI in the pharmaceutical field, including statistical optimization methods, quality by design, machine learning algorithms, applications of AI in the pharmaceutical field, and precision medicine. In addition, we also discuss the current challenges and future prospects in the pharmaceutical industry.