The Impact of Artificial Intelligence on Sustainable Agriculture: Developing Advanced Computing Models for Environmental and Economic Benefits

Abstract

This research explores the transformative impact of artificial intelligence (AI) on sustainable agriculture, focusing on the development and application of advanced computing models that deliver environmental and economic benefits. AI technologies, including machine learning, deep learning, computer vision, and robotics, offer significant improvements over traditional agricultural practices by analyzing complex datasets to uncover patterns, predict outcomes, and automate processes. Precision farming, AI-driven livestock management, and supply chain optimization illustrate how AI can enhance resource efficiency, reduce environmental impacts, and increase crop yields and profitability. Case studies demonstrate significant benefits: optimized irrigation reduces water usage by up to 45%, early pest detection decreases pesticide use by 50%, and AI-based supply chain systems reduce post-harvest losses by 40%. Despite these advantages, challenges such as high initial investment costs, limited access to technology, and the need for high-quality data remain. Addressing these barriers through targeted policies, capacity-building initiatives, and ethical considerations is crucial for widespread AI adoption. Future research should focus on developing scalable AI solutions and fostering interdisciplinary collaboration. This study highlights AI's potential to revolutionize agriculture, balancing productivity with environmental stewardship, and paving the way for a sustainable agricultural future.