ARTIFICIAL INTELLIGENCE AND DIGITAL TRANSFORMATION OF AGRICULTURE: A PATHWAY TO SUSTAINABLE DEVELOPMENT

Abstract

The study examines the prospects of digital transformation and the application of Artificial Intelligence (AI) in modern agriculture as a response to global challenges of food security, climate change, and resource scarcity. The main purpose is to analyze how AI-based technologies—such as machine learning, IoT, and predictive analytics—enhance agricultural efficiency, sustainability, and decision-making. The research employs an analytical and comparative approach based on recent literature and global case studies from the United States, the European Union, China, and India. Findings indicate that AI enables precision irrigation, optimized resource allocation, and improved yield prediction, thereby reducing costs and environmental impact. However, barriers such as low digital literacy, limited infrastructure, and insufficient investment remain pronounced in developing economies. The case of Azerbaijan illustrates both emerging potential and persistent challenges in implementing smart agriculture initiatives. The study concludes that successful AI integration requires coordinated policy frameworks, digital capacity-building, and multi-sector collaboration to achieve sustainable agricultural transformation.