AI in nutrition: multi-criteria analysis of diet plans across diverse client profiles

The advancement of artificial intelligence (AI) technologies has resulted in the proliferation of novel applications in various fields, including nutrition. One of the most notable applications involves AI-generated and guided diet plans. The present study evaluates diet plans generated by various AI tools (e.g., ChatGPT, Gemini, DeepSeek, etc.) for individuals with different health profiles using a multi-criteria decision-making (MCDM) framework. A series of authentic client scenarios were formulated on the basis of anonymized clinical cases that had been provided by a registered dietitian. These scenarios incorporated medical history, lifestyle habits, dietary patterns, and other relevant factors. For each client's profile, a set of standardized prompts were submitted to different AI tools to generate comparable diet plans. The resulting diet plans were evaluated based on several main and sub-criteria, including appropriateness, feasibility, nutritional adequacy, degree of personalization, ethical compliance, reproducibility, and linguistic clarity. The evaluation employed MCDM methods, namely LBWA for weighting, COPRAS, and PROMETHEE-I/II for ranking. The findings indicate that GPTPLUS demonstrated the highest overall ranking; DeepSeek exhibited consistent second-tier performance; and mid-tier models (GPT-4.0, GPT-4.5, Grook3) exchanged positions depending on the scenario and method. The results at the criterion level were found to be aligned with clinical priorities. Moreover, Claude's refusal to formulate a dietary plan for a client under the age of 18 indicates a paucity of standardized ethical guidelines governing the utilization of AI tools. The findings emphasize the potential of AI as a supportive tool in healthcare services, while concurrently addressing ethical considerations and practical limitations.