This study explores the transformative potential of Artificial Intelligence (AI) in promoting sustainable agricultural practices. AI-driven technologies, particularly in precision agriculture, offer promising solutions for enhancing resource efficiency, crop monitoring, and decision-making processes. By leveraging machine learning and computer vision algorithms, AI can optimize the use of inputs such as fertilizers, pesticides, and water, increasing productivity while minimizing environmental impact. Integrating AI in agriculture also presents significant socio-economic benefits, including improved profitability for farmers and enhanced food security. However, the adoption of AI technologies raises critical ethical and environmental concerns, such as data privacy, algorithmic bias, and potential unintended ecological consequences. This comprehensive review aims to provide a holistic analysis of the technological, social, economic, ethical, and environmental dimensions of AI in sustainable agriculture. The study synthesizes findings from current literature and empirical research to offer a framework for the responsible and equitable integration of AI technologies. By addressing the challenges and opportunities associated with AI adoption, this research seeks to ensure that the benefits of technological advancements are accessible to all stakeholders, particularly small farmers, and marginalized communities. The goal is to promote inclusive agricultural development that supports social justice, environmental sustainability, and broad-based economic growth.