Artificial intelligence (AI), machine learning (ML), and deep learning (DL) are promising tools that can be used to develop algorithms to better understand and predict interactions between food- and nutrition-related data and health outcomes. Understanding that additional research is needed to identify areas where AI/ML is likely to have an impact, the National Academies Food and Nutrition Board hosted a public workshop in October 2023 to explore the future benefits and limitations of integrating big data and AI/ML tools into nutrition research. Participants also discussed issues related to diversity, equity, inclusion, bias, and privacy and the appropriate use of evidence generated from these new methods.Table of ContentsFront Matter1 Introduction2 Setting the Stage3 Applications and Lessons Learned4 Capacity Building5 Potential Applications of AI to Large-Scale Food and Nutrition Initiatives6 Final Discussion and SynthesisReferencesAppendix A: Workshop AgendaAppendix B: Biographical Sketches of the Speakers and Moderators