AI-Driven Smart Agriculture And Food Security In Developing Countries: A Comparative Perspective

Agriculture remains a cornerstone of economic development and food security in many developing countries. However, the sector continues to face challenges such as climate change, declining natural resources, labour shortages, and increasing production costs. Recent advances in artificial intelligence (AI) and smart agriculture provide new opportunities to improve agricultural productivity, optimize resource use, and strengthen food security. This study examines the role of AI-driven smart agriculture in enhancing food security through a comparative analysis of India, China, Brazil, Vietnam, Kenya, and Indonesia. The findings reveal considerable differences in AI readiness and the adoption of smart agricultural technologies among the countries. Nations with stronger digital infrastructure and higher AI readiness demonstrate greater adoption of precision farming practices and better food security outcomes. The study concludes that expanding digital infrastructure, improving farmers' access to AI-based technologies, strengthening technical capacity, and encouraging collaboration among governments, research institutions, and agritech firms are essential for achieving sustainable agricultural development and improving food security in developing countries. The novelty of this study lies in integrating AI readiness, digital infrastructure, precision farming adoption, and food security into a comparative analysis of six developing countries using 2024 secondary data.