Using Agile in Implementing Agriculture AI Projects and Farm Management




Agile farm management, Artificial Intelligence (AI), Agriculture, Flexibility, Continuous improvement, Collaboration, Scrum, Iterative planning, Crop management, Efficiency, Productivity, Sustainability, Decision-making capabilities, Advanced management techniques


The world's population has been increasing rapidly at an unprecedented rate In recent decades. This increase poses significant challenges to the agricultural and farming sector. With more mouths to feed, old farming techniques can’t meet the demand. It has become increasingly crucial to adopt advanced management techniques and cutting-edge technologies to boost agricultural productivity, reduce harvesting waste and meet the growing demand for food.
This necessitates a paradigm shift in managing farms and agriculture, moving from traditional methods to more innovative and efficient approaches. Two approaches that have recently gained considerable attention are Agile management and Artificial Intelligence (AI). Farmers and agricultural managers can streamline their operations, increase efficiency, and improve their decision-making capabilities by adopting Agile and AI. This paper aims to explore the unique benefits and challenges of implementing Agile management and AI technologies in the agricultural sector and provide insights into their potential to revolutionise the industry. A theoretical implementation model was created with tips and guides for implementation.

Author Biography

Hasan AlJafa, University of Debrecen

PhD Student in Management and organization




How to Cite

AlJafa, H., & László, V. (2023). Using Agile in Implementing Agriculture AI Projects and Farm Management. Journal of Agricultural Informatics, 14(1).



Journal of Agricultural Informatics