Zambia
Kenia
Artificial Intelligence (AI) is revolutionizing agricultural economics by optimizing productivity, reducing costs, and enhancing decision-making processes. This paper explores the integration of AI technologies—such as machine learning, predictive analytics, and automation—into agricultural economic frameworks. AI-driven innovations, including precision farming, yield forecasting, and supply chain management, are reshaping agricultural practices by improving efficiency and sustainability. Furthermore, AI facilitates data-driven policymaking, enabling governments and stakeholders to address food security, market fluctuations, and resource allocation more effectively. Despite its benefits, AI adoption in agriculture faces challenges, including high implementation costs, data privacy concerns, and the digital divide between developed and developing regions. The study highlights case studies and real-world applications demonstrating AI’s impact on economic growth and sustainable agricultural development. The findings suggest that strategic investment in AI infrastructure, combined with supportive policies and education, can accelerate its adoption and maximize its economic benefits. Ultimately, AI integration holds the potential to transform agricultural economies by fostering innovation, resilience, and sustainability.
© 2001-2025 Fundación Dialnet · Todos los derechos reservados