THE USE OF ARTIFICIAL INTELLIGENCE IN NUTRITIONAL SERVICES: ADVANCES AND PERSPECTIVES

Abstract

Artificial intelligence (AI) is a field of computer science that seeks to simulate human cognitive processes, such as learning, reasoning, and decision-making, through algorithms capable of analyzing large volumes of data, identifying patterns, and supporting actions in different fields, including nutrition. In nutritional practice, AI contributes to more accurate diagnoses, management in food and nutrition units (UANs), development of public policies, and nutritional surveillance, optimizing resources and promoting more effective health outcomes. The technology makes it possible to classify dietary, biochemical, and behavioral data, as well as to apply methods such as neural networks, machine learning, and random forest to predict, categorize, and suggest interventions. However, its use presents challenges such as scientific and ethical validation, combating bias, protecting data privacy, and disseminating knowledge among professionals. Despite offering speed and breadth of results, AI may restrict analyses by working only with previous data, failing to capture cultural, emotional, and contextual nuances essential for individualized nutritional care. Therefore, it should serve as a complementary tool to human reasoning, keeping the nutritionist as a critical and decisive agent. In the field of public health, intelligent systems already collaborate in school feeding programs, in combating metabolic diseases, and in reducing food waste, moving closer to the Sustainable Development Goals (SDGs) by integrating public, private, and civil society sectors. Nevertheless, there are still obstacles such as the lack of professional training and the risk of distortions through inappropriate marketing use. Thus, AI represents a strategic advance in food security, clinical care, and health promotion, but it must be monitored to ensure that its applicability generates real and sustainable benefits.