Research Paper On- Artificial Intelligence in Agriculture: Opportunities, Challenges and Policy Implications

Abstract

Artificial Intelligence (AI) is emerging as a transformative force in the agricultural sector by improving productivity, optimizing resource utilization, and promoting sustainable farming practices. The integration of AI technologies such as machine learning, computer vision, robotics, Internet of Things (IoT), and big data analytics has enabled precision agriculture, smart irrigation systems, yield prediction models, pest and disease detection, and supply chain optimization. In countries like India, where agriculture remains a major source of livelihood, AI has the potential to address structural issues such as low productivity, climate variability, fragmented landholdings, and market inefficiencies. AI-powered platforms assist farmers in real-time decision-making by analyzing weather data, soil conditions, crop health, and market trends. Despite its transformative potential, the adoption of AI in agriculture faces several challenges including high initial costs, inadequate digital infrastructure, lack of technical awareness, data privacy concerns, and limited access to quality datasets. This research paper examines the role of AI in agriculture, evaluates its economic and social implications, and identifies the challenges associated with its implementation. The study concludes that effective policy support, public-private partnerships, capacity-building initiatives, and digital infrastructure development are crucial to maximizing the benefits of AI in agriculture.