A.I. in Agriculture – A Bibliometric Approach

Panciu Bogdan-Ionuț () and Barbu Dragne Gabriela-Larisa ()
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Panciu Bogdan-Ionuț: Bucharest University of Economic Studies, Bucharest, Romania
Barbu Dragne Gabriela-Larisa: Bucharest University of Economic Studies, Bucharest, Romania

Proceedings of the International Conference on Business Excellence, 2025, vol. 19, issue 1, 5189-5199

Abstract: The aim of this paper is to analyze the connection between Artificial Intelligence and agriculture from a bibliometric approach. The main goal is to showcase the newest trends and the evolution of research in this domain. The fast development of A.I. technologies and its integration are more frequent in many diverse sectors, including agriculture. Therefore, the potential of implementing A.I. may help in resolving global problems, like global food security, the management of resources and also climate changes. Looking at a rising population level worldwide and the challenges that the food chains face, Artificial Intelligence may come as an opportune and efficient solution in optimizing agricultural processes. The method used in this research consists in a bibliometric analysis, which was conducted based on the data from the Web of Science database. A total number of 14,482 documents were first identified, and after further filtering based on categories, 6,883 documents remained. The analysis took into account many important indicators, like the number of scientific papers published, the authors the authors with highest contributions and also the geographical distribution of research. The results imply a significant growing interest regarding A.I. in agriculture, especially after the year 2020, fact that highlights the growing importance of digitization in this field. This emphasizes the role of A.I. in developing productivity, sustainability and improving the decision-making processes in agriculture. This paper concludes that A.I. is helpful in agriculture and that this study can provide solid insights in understanding the current research trends and future similar studies.

Keywords: artificial intelligence; a.i.; agriculture; bibliometric analysis; co-occurrence; food security. (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:poicbe:v:19:y:2025:i:1:p:5189-5199:n:1046

DOI: 10.2478/picbe-2025-0397

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