The past decade has seen continued development in artificial intelligence (AI). ChatGPT made AI accessible to the public en masse in 2022 and its improved training capabilities utilising images and code, and multimodal outputs meant the latest version was widely embraced. Consequently, academics, researchers and nutrition professionals are rushing to comprehend the positive and negative implications for their work and to understand data accessibility and concerns around privacy and ethical use. A quick search in my university approved AI tool ‘Copilot’ reveals generative AI may be useful in nutrition such as summarising scientific articles or making tailored eating plans for individuals. A key step to designing individual and population nutritional recommendations is assessment of dietary intake. Last century four basic tools of dietary assessment were developed and this century we have seen growth in technology-assisted iterations of the original methods. Machine learning and algorithms were harnessed for 24 h recalls and image-based food records, but now we see generative AI can further enhance these tasks. Commercial and research apps collect images and use AI to determine nutrient content, and some will offer nutrition advice. ChatGPT has been used as the dietary assessment tool in some studies. Chatbots deliver accurate nutrition advice for general nutritional information. However, for more nuanced information, especially medical nutrition therapy, provision of integrated personalised care was markedly inferior and inaccurate to that offered by the nutrition health professional. Nevertheless, further advances in AI will increasingly be useful to nutrition research and practice when used ethically.