What does this research mean for the field?

Artificial intelligence serves as a valuable clinical co-pilot that enhances the nutrition care process and food service management, provided dietitians maintain a human-in-the-loop approach and adhere to ethical and regulatory frameworks. Novelty: ClaimNovelty.SYNTHESIS. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

The review investigates how AI technologies can enhance dietetic practices and address ethical challenges.

June 20, 2026Open Access

The role of artificial intelligence in dietetic practice: a narrative review of current evidence and practical applications

Key Points

The review investigates how AI technologies can enhance dietetic practices and address ethical challenges.
Narrative review of current evidence on AI in dietetics.
Analysis of AI subfields such as machine learning and natural language processing.
Examination of regulatory challenges faced by Registered Dietitians in South Africa.
AI-driven tools improve dietary assessments and malnutrition screening.
Emerging applications in food service management show potential for reducing food waste.
Risks associated with AI include algorithmic bias and the need for regulatory compliance.

Abstract

Background: The global nutrition landscape is shifting from population-based advice towards hyper-personalised clinical care, driven by a ‘data drown’ from wearable sensors and digitised health records. Artificial intelligence (AI) has emerged as a pivotal assistive technology to navigate this complexity, transitioning from a theoretical construct to a practical clinical ‘co-pilot’.Objective: This review explores the integration of AI subfields, including machine learning (ML), deep learning (DL), and natural language processing (NLP), into the nutrition care process (NCP), and the specific regulatory and ethical landscape facing South African Registered Dietitians (RDs).Discussion: AI-driven tools enhance the NCP by improving the accuracy of dietary assessments through computer vision, automating malnutrition screening via predictive modelling and optimising high-stakes interventions such as total parenteral nutrition (TPN) in neonatal care. Additionally, the review examines emerging applications of AI in institutional food service management, including intelligent menu planning, automated procurement and food waste reduction, domains that are integral to the South African Registered Dietitian’s scope of practice but have received comparatively limited attention in the literature. However, the transition to AI-augmented practice introduces risks of algorithmic bias, ‘de-skilling’ and AI ‘hallucinations’. Within the South African context, practitioners must navigate stringent requirements set by the Health Professions Council of South Africa (HPCSA) Booklet 20 and the Protection of Personal Information Act (POPIA). The use of clinical-grade prompt engineering, such as the PCCF (Persona, Context, Constraints, and Format) framework, is presented as a vital competency to ensure medically and culturally appropriate outputs.Conclusion: AI should be positioned as a clinical co-pilot that amplifies the impact of the dietitian rather than a substitute for professional autonomy. By maintaining a ‘human-in-the-loop’ approach and adhering to local regulatory frameworks, South African dietitians can leverage AI to address the nation’s unique nutritional double burden and promote health equity.

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