Integrating Emerging Digital and AI-Based Dietary Assessment Tools with Traditional Methods: Advancements and Challenges

Dietary assessment is essential in supporting nutritional monitoring, clinical care and planning health programs for the community. Despite being traditional ways to gather data, such as food frequency questionnaires (FFQs), 24-hour dietary recalls, and food diaries have a high risk of memory bias and can be inaccurate. Digital technologies that use AI help design new methods for measuring what people eat with increased precision, scalability, and user engagement. This review brings together information from 18 open-access research articles (2020–2025) to compare digital and AI-based assessment tools to the traditional methods used in the nutrition care setting. Thus, exploring their respective strength, weakness, barriers to adopt it on wide scale, the issues they encounter, how they are used in clinical practice and if they can be used in combination. The article emphasizes that AI-based instruments have become much more accurate, they are being used more in clinics and communities, but adoption is hindered by concerns over privacy, getting patients to use them and potential biases in the technology. A unified strategy is put forward to promote responsible, expandable and successful use of both AI and traditional methods in dietary assessments.