<![CDATA[Stunting remains a serious public health problem in Indonesia. Although the prevalence of stunting has shown a downward trend in recent years, it remains at a level that requires ongoing attention and intervention. The First 1000 Days of Life (HPK) program has become the government's primary strategy for preventing stunting from pregnancy to two years of age. However, the program's implementation still faces various obstacles, such as limited access to information, poor quality child growth monitoring, suboptimal early detection systems, and limited health data integration. This article aims to develop a conceptual model for stunting prevention based on Artificial Intelligence (AI) and digital technology as an innovative approach to support the effectiveness of the 1000 HPK program in Indonesia. The research uses a conceptual method with a literature review approach of various research, policies, and developments in digital health technology. The study results show that integrating AI into the health system can improve the ability to predict stunting risks, strengthen maternal and child health monitoring systems, provide more personalized nutrition recommendations, and enhance the effectiveness of data-driven decision-making. The developed model consists of five main components: digital data collection, AI-based predictive analysis, an early warning system, personalized health interventions, and ongoing evaluation. Implementing this model has the potential to accelerate the achievement of the national stunting reduction target while supporting the digital transformation of the health sector in Indonesia.]]>
