Artificial Intelligence (AI) is a broad concept of training machines to think and behave like humans. It consists of a wide range of statistical and machine learning approaches to learn from the existing data/information to predict future outcomes. AI has impacted a board range of scientific disciplines that are important to public health, ranging from clinical diagnosis and prognosis, drug and food safety, disease prevention, precision medicine and nutrition. The rise of AI has also offered both opportunities and challenges to regulatory agencies with questions such as (1) how to assess and evaluate AI-based products and (2) how to develop and implement an AI-based application to improve the agencies functions. In this presentation, the current thinking and on-going efforts at the FDA’s National Center for Toxicological Research (NCTR) in the area of AI will be discussed with examples from drug and food safety, natural language processing of regulatory documents, and biomarker discovery and development. The guiding principle and best practice of applying AI in regulatory science research will also be discussed with respect to the context of use and fit-for-purpose application.