This study systematically reviews the transformative role of Artificial Intelligence (AI) in enhancing agricultural productivity and sustainability in the United States. With the aim of understanding how AI technologies can be effectively integrated into farming practices, this research employs a systematic literature review methodology, focusing on peer-reviewed journal articles, conference proceedings, and reputable reports from 2010 to 2024. The methodology includes a structured search strategy, defined inclusion and exclusion criteria, and thematic analysis to categorize findings into relevant themes. Key findings reveal that AI technologies, such as machine learning models, predictive analytics, and robotics, are revolutionizing U.S. agriculture by optimizing resource use, improving crop health monitoring, and enhancing decision-making processes. Despite the promising potential of AI to address challenges like food security and environmental sustainability, the adoption of AI in agriculture faces barriers including technological adoption, data privacy concerns, and the need for significant investment in digital infrastructure. The study concludes that leveraging AI for sustainable agriculture requires collaborative efforts among stakeholders, including investment in digital literacy, development of regulatory frameworks, and fostering public-private partnerships. Future research directions emphasize the socio-economic impacts of AI adoption, ethical considerations, and the development of scalable AI solutions. This study underscores AI's pivotal role in ensuring a sustainable, productive, and resilient agricultural sector.