Extension Workers’ Attitudes toward Employing Artificial Intelligence in Contract Farming: Effects on Sustainable Rural Development in Egypt

Mamdouh, Ola; Mohamed, Heba Nor- Eldin; Mohamed, Rabab Said

doi:10.21608/alexja.2025.438514.1177

Extension Workers’ Attitudes toward Employing Artificial Intelligence in Contract Farming: Effects on Sustainable Rural Development in Egypt

Articles in Press

Document Type : Original Article

Authors

¹ Department of Rural Sociology and Agricultural Extension, Faculty of Agriculture, Ain Shams University, Egypt

² Department of Agricultural Economics and Extension, Faculty of Agriculture, Benha University

10.21608/alexja.2025.438514.1177

Abstract

The main objective of this research is to examine the attitudes of extension workers toward employing artificial intelligence (AI) in contract farming and to analyze its implications for sustainable rural development in Egypt, in light of the accelerating digital transformation in the agricultural sector. The study adopted a descriptive-analytical approach, and data were collected from a sample of 66 extension workers from different governorates using a specially designed questionnaire. Data were analyzed using appropriate statistical methods, including frequencies, percentages, means, standard deviations, simple correlation coefficients, and stepwise multiple regression analysis. The results revealed that the overall attitude of extension workers toward employing AI in contract farming was moderately positive, tending toward a higher level, with a mean score of 3.43 out of 5, representing 68.6%. The main constraints limiting the use of AI were the lack of technical resources (87.9%), farmers’ resistance to change (81.8%), insufficient training (78.8%), and inadequate technical support (75.8%). Correlation analysis showed significant positive relationships at the 0.01 level between the overall attitude and each of the following variables: years of experience, achievement motivation, educational level, and internet accessibility. Collectively, these variables explained about 95.91% of the total variance in attitude. Respondents also suggested several practical measures to enhance AI adoption, including the provision of digital infrastructure, intensifying training programs, developing continuous technical supervision, and preparing simplified educational materials for farmers

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