Artificial Intelligence in Agriculture

Technological Foundations, Adoption Drivers and Labor Market Implications
Erscheinungsjahr 2026
ISBN: 978-3-032-26579-1
Verlag: Springer

Buch, Englisch, 148 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 416 g

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.

Zielgruppe

Research

Autoren/Hrsg.

Apicella, Andrea

Fachgebiete

• Wirtschaftswissenschaften Wirtschaftssektoren & Branchen Primärer Sektor
• Wirtschaftswissenschaften Volkswirtschaftslehre Volkswirtschaftslehre Allgemein Arbeitsmarkt
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Naturwissenschaften Agrarwissenschaften Agrarwissenschaften

Inhaltsverzeichnis

1. Introduction The Digital Transformation of Agriculture From Data to Generative AI.- 2. Precision Agriculture and Artificial Intelligence: A Global Literature Review of Applications, Adoption Gaps, and Enabling Technologies.- 3. Adoption Drivers, Barriers and Risks: A Comparative Analysis of Smallholder and Large-Scale Farms.- 4. Labour Market Shifts and Job Creation in AI-Driven Agriculture.- 5. Digital Skills and Training Pathways for the AI-Enabled Agricultural Workforce.- 6. Policy Pathways for Inclusive, Ethical and Sustainable AI in Agriculture.

Über Autor(innen)

holds a PhD in Business Administration and Management. His research focuses on artificial intelligence and digital innovation in agri-food systems, with particular emphasis on precision agriculture, sustainability, and supply chain transformation. He is the author of numerous scientific publications on technological adoption and the ecological transition of agriculture, contributing to the international academic debate through conferences and research initiatives.