Artificial Intelligence in Agriculture
Technological Foundations, Adoption Drivers and Labor Market Implications
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Beschreibung
This book explores the transformative impact of Artificial Intelligence (AI) on precision agriculture and rural labor markets, critically analyzing the adoption dynamics of AI tools, such as machine learning, computer vision, and expert systems, while addressing broader socio-economic implications, particularly related to employment transformation and digital skills development. It offers a comprehensive, literature-based assessment of how AI, ranging from classical machine-learning approaches to the latest generative-AI systems, is reshaping precision agriculture across both crop and livestock production. The book moves beyond technical descriptions to examine adoption dynamics, labor-market effects, skills and training needs, and policy pathways. By integrating technological, socio-economic and policy perspectives, the volume aims to serve researchers, educators, technology providers and decision-makers seeking an evidence-based roadmap for responsible AI adoption in agriculture over the next two decades.
This book explores the transformative impact of Artificial Intelligence (AI) on precision agriculture and rural labor markets, critically analyzing the adoption dynamics of AI tools, such as machine learning, computer vision, and expert systems, while addressing broader socio-economic implications, particularly related to employment transformation and digital skills development. It offers a comprehensive, literature-based assessment of how AI, ranging from classical machine-learning approaches to the latest generative-AI systems, is reshaping precision agriculture across both crop and livestock production. The book moves beyond technical descriptions to examine adoption dynamics, labor-market effects, skills and training needs, and policy pathways. By integrating technological, socio-economic and policy perspectives, the volume aims to serve researchers, educators, technology providers and decision-makers seeking an evidence-based roadmap for responsible AI adoption in agriculture over the next two decades.
Offers a comprehensive assessment of how artificial intelligence is reshaping precision agriculture Provides an evidence-based roadmap for responsible AI adoption in agriculture Presents recommendations on data governance, rural broadband and “green-AI” incentives aligned with the SDGs
Autor*in
Andrea Apicella
Themen in »Artificial Intelligence in Agriculture«
AI in precision agriculture Large-language models in farming Agri-food systems Rural connectivity Crop and livestock analytics Agricultural monitoring Inclusive AI Interoperability standards