Legal Challenges and Policy Implications of AI-Enabled Precision Livestock Farming in Developing Countries

Abstract

Artificial intelligence (AI)-enabled Precision Livestock Farming (PLF) is transforming livestock production through intelligent monitoring, predictive analytics, automated decision-making, and resource optimization. However, its rapid adoption in developing countries has introduced complex legal, ethical, and policy challenges that hinder responsible implementation. This review critically examines the evolving legal landscape governing AI-driven PLF, focusing on data ownership, privacy protection, algorithmic accountability, intellectual property rights, animal welfare regulations, and cross-border data governance. The study systematically analyzes existing literature, international regulatory initiatives, and national policy frameworks to identify key legal gaps and governance limitations affecting developing economies. Furthermore, it compares AI governance models and regulatory approaches adopted across different jurisdictions, highlighting their applicability, strengths, and implementation challenges within resource-constrained agricultural systems. Based on this comparative assessment, a comprehensive policy and regulatory framework is proposed that integrates risk-based AI governance, transparent data-sharing mechanisms, ethical compliance, institutional capacity building, and standardized certification practices. The review concludes that harmonized legal frameworks, adaptive regulatory mechanisms, and coordinated stakeholder participation are essential for ensuring trustworthy, equitable, and sustainable AI adoption in livestock farming while supporting food security, innovation, and long-term agricultural development in developing countries.