Food and drug safety is essential to human lives, as contaminated food or unregulated drugs can affect health, physical growth, and cognitive development. Recent innovations in technological development have generated artificial intelligence (AI), particularly machine learning (ML) and deep learning (DL), to improve the safety of food and drugs, both at the pre-market and post-market stages. The purposes of this study are: 1) to identify the potential roles of AI in food and drug safety areas from administrating to monitoring and evaluation; and 2) to address the problems and challenges in adopting AI in food and drug safety. Using a systematic literature review, this study captures the panoramic view of the literature discussing the application of AI to ensure the security of food and pharmaceuticals. Based on 36 qualifying studies published in 2017-2024, this study reveals that AI supports enhancing food and drug safety by predicting risks, identifying hazards, enhancing quality control, and improving monitoring and evaluation. The challenges in AI lie in the characteristics and quality of data, complexity in model interpretation, technological barriers, and ethical, societal, and regulatory challenges.