Artificial intelligence (AI) and machine learning may revolutionize the design and evaluation of public health interventions by enabling advanced data analysis techniques, including the exploration of cultural dimensions that shape the actions addressing health-related behaviors. Promoting healthy lifestyles—such as proper nutrition, regular physical activity, and the reduction of behavioral risk factors like smoking, alcohol consumption, and sedentary behavior—is central to global efforts in preventing chronic non-communicable diseases, the primary contributors to global mortality and reduced healthy life expectancy. In Italy, the Ministry of Health has supported health promotion projects through the National Center for Disease Prevention and Control (CCM) since 2004. This study integrates AI-driven methodologies, particularly Emotional Text Mining, to explore the symbolic-cultural categories and representations underlying these interventions. By decoding the language and narratives present in project documentation, the study identifies patterns and cultural dimensions that influence the planning and perceived effectiveness of health promotion initiatives. This approach aligns with current advancements in AI, which unveil hidden connections in complex data networks, providing insights into the societal and environmental factors affecting public health strategies. The results offer a foundation for identifying predictive indicators of intervention impact, enabling a link between textual analysis and effective and feasible public health actions. This study aims to foster a deeper understanding of how AI can enhance the sustainability and effectiveness of health policies, contributing to the broader dialogue on AI-driven communication and collaboration networks for societal and ecological well-being.