Hartmann, NicolasNicolasHartmannSprengholz, PhilippPhilippSprengholz0000-0002-9925-19202026-08-102026-08-1020262048-7177https://fis.uni-bamberg.de/handle/uniba/116678Food-based dietary guidelines (FBDGs) are a key instrument for communicating healthy nutrition principles that are implemented in most countries. However, adherence remains low, and recent literature highlights the need for improvements. This exploratory study investigated consumer perceptions of the German FBDGs, focusing on strengths and areas for improvement. Ten individuals with diverse demographics, nutrition knowledge, and dietary motivation participated in semi-structured interviews. Participants evaluated the content and design of the FBDGs regarding both comprehensibility and applicability. Additionally, participants provided feedback on a proposed mock-up illustrating the concept of an AI-based feedback tool aimed at enhancing individualization and contextual aspects. Overall, participants expressed more criticism than approval. Although the FBDGs were generally considered easy to understand, many found them difficult to translate into daily practice. Participants perceived the FBDGs as (a) too general for individualized diets and (b) too theoretical, offering little support for behavior change. Positive feedback mainly referred to the simple and understandable language. The mock-up was received more positively, though some criticism regarding individualization was raised. The findings suggest that while the German FBDGs effectively illustrate healthy eating principles conceptually, they fall short in supporting real-life implementation. The presented AI-based tool represents a promising step toward more practical and individualized guidance but may still not be sufficient to induce substantial changes to behaviors. Future improvements to national dietary guidance may therefore require the development of complementary, behaviorally oriented programs that go beyond informational approaches and address the practical realities of everyday nutrition.engartificial intelligenceconcept evaluationfood-based dietary guidelinesnutrition communicationqualitative researcharticle10.1002/fsn3.72242