# Artificial intelligence diet plans underestimate nutrient intake compared to dietitians in adolescents

## TL;DR

AI-generated diet plans for adolescents underestimate nutrient intake compared to plans made by dietitians, suggesting a need for professional oversight.

## Contribution

This study is the first to systematically compare AI-generated adolescent diet plans with dietitian-recommended ones, revealing significant underestimation of nutrients.

## Key findings

- AI models systematically underestimated energy and macronutrient intake compared to dietitian plans.
- Micronutrient content varied significantly between AI models, with no model consistently matching dietitian recommendations.
- Carbohydrate ratios in AI plans were below recommended guidelines for adolescents.

## Abstract

Although artificial intelligence (AI)-based nutrition recommendations are becoming increasingly common among the public, the accuracy and reliability of diets produced especially for adolescents in the growth and development period are not sufficiently known. This study aimed to evaluate the clinical validity of AI by comparing the nutritional content of diets generated by different AI models with dietitian reference plans.

A total of 60 three-day diet plans were generated in two sessions by five AI models (ChatGPT-4o, Gemini 2.5 Pro, Claude 4.1, Bing Chat-5GPT, and Perplexity) for four standardized adolescent profiles in this cross-sectional and comparative study. A dietitian reference plan was prepared for each profile. Energy and macro-micronutrients were analyzed with BeBiS. Comparisons were evaluated with single-sample t-test, Cohen’s d, and Bland–Altman fit analyses.

AI models tended to systematically undercalculate energy (bias: +695 kcal), protein (+19.9 g), lipid (+15.8 g), and carbohydrate (+114.6 g). In macronutrient percentages, protein (21.5–23.7%) and lipid (41.5–44.5%) ratios were above the recommended adolescent guidelines, while carbohydrate ratios (32.4–36.3%) were significantly below. Significant variation was observed between models in micronutrient contents, and no model showed consistent proximity to the dietitian across all nutrients.

AI models have exhibited clinically significant deviations in diet plans for adolescents at both macro and micro levels. The findings indicate that AI-based dietary recommendations are not appropriate to use without professional supervision, emphasizing the need for model improvements for more reliable data generation in this area.

Infographic comparing adolescent diet plans from artificial intelligence models and registered dietitians, illustrating methodology, four test profiles, and results showing AI underestimation of energy and macronutrients, wide variability, and superior consistency from dietitians.