Artificial Intelligence in Sustainable Agriculture: Optimizing Crop Yields and Reducing Environmental Impact in the USA

Abstract

Artificial Intelligence (AI) is rapidly transforming various sectors, and agriculture is no exception. In the context of sustainable agriculture, AI offers significant potential to optimize crop yields, reduce environmental impacts, and improve resource efficiency. This paper explores the integration of AI technologies in agriculture in the United States, focusing on applications in precision farming, crop monitoring, soil health management, and pest control. By utilizing AIdriven solutions such as machine learning, computer vision, and remote sensing, farmers can make data-driven decisions that enhance crop productivity while minimizing the use of water, fertilizers, and pesticides. This study also examines the challenges associated with the implementation of AI technologies in agriculture, including the accessibility of data, computational infrastructure, and the need for widespread adoption of digital tools. The paper concludes by highlighting the role of AI in creating a more sustainable agricultural system, capable of meeting the food demands of a growing population while protecting the environment.