Advancements in technology, particularly in the realm of artificial intelligence (AI), have led to innovative applications across various domains, including healthcare and dietary monitoring. The chapter delves into the intersection of AI and nutrition, specifically focusing on monitoring and optimizing of nutrient intake and highlighting the potential for AI-driven solutions to revolutionize how individuals track, analyze, and enhance their nutritional habits. The discussion commences with an overview of prevalent challenges in conventional nutrient monitoring methods and their limitations. Subsequently, it explores the integration of AI algorithms and machine learning techniques in processing vast amounts of dietary data. AI’s capability to analyze dietary patterns, recommend personalized meal plans, and predict nutritional deficiencies offers promising avenues for improving overall health and well-being. Moreover, the chapter examines the utilization of AI-powered applications and devices, ranging from mobile apps to smart kitchen appliances, designed to assist users in making informed dietary choices. These technological interventions facilitate real-time tracking, personalized recommendations, and feedback mechanisms, empowering individuals to optimize their nutrient consumption effectively. Furthermore, ethical considerations and potential challenges in AI-driven nutrient intake monitoring are addressed, including data privacy, algorithm biases, and the need for interdisciplinary collaboration. This book chapter underscores the transformative potential of AI in revolutionizing how we monitor and optimize nutrient consumption, thereby contributing to improved health outcomes and fostering a deeper understanding of personalized nutrition strategies.