AI Enabled ICDS to Combat Malnutrition: Challenges, Opportunities, and the Path Forward

ICDS has been India's flagship healthcare system in tackling malnutrition. The services provided by the scheme have made significant progress in addressing the problem of malnutrition, but according to the National Family Health Survey (NFHS-5), 35.5 % of children under 5 years of age are stunted, 19.3 % suffer from wasting, and 32.1% are underweight. Current data on malnutrition are a major concern for Indian policy designers. This paper analyzes the present ICDS framework and highlights the impact of AI tools adopted in different Indian states. The study finds challenges, opportunities, and future directions in the context of the employability of AI in ICDS services. The findings of various states indicate that the use of AI tools such as AI-enhanced data analysis, IoT, and predictive analysis can reduce different forms of malnutrition by up to a maximum of 25%. AI tools such as ML algorithms, predictive analytics, and data-driven decision support systems can improve the limitations of the current ICDS framework. This paper also suggests an AI-enabled ICDS framework and discusses ICDSspecific concerns about data privacy, algorithm bias, and ethical issues.