Building meaning in agricultural management in the face of artificial intelligence as a disruptive technology

Abstract

This study aims to interpret the daily practices and dynamics of agricultural management in companies located in the Municipality of Colón, Zulia State, Venezuela, in response to the incorporation of Artificial Intelligence as a disruptive technology. Methodologically, the research was conducted using a qualitative approach, specifically ethnomethodology. The key participants included five individuals: managers, agricultural producers, agricultural technicians or advisors, and heads of technological or innovation departments in agricultural companies. They were interviewed using a semi-structured questionnaire, allowing participants the option to elaborate on their answers. Data analysis was carried out through Grounded Theory, employing open, axial, and selective coding. This process enabled an interpretation of agricultural management as a meaning-making construction that goes beyond a traditional academic definition, encompassing subjective experiences that blend leadership, operational functionality, economic sustainability, and environmental adaptability. In this sense, it represents a notion built from the rural context, where classical models, emerging practices, and hybrid work organization experiences converge. Within this context, Artificial Intelligence is not presented as an autonomous agent of change but rather as a relational device. Accordingly, the present study offers an interpretative framework to understand that technological disruption does not occur in neutral territories, but rather in landscapes deeply woven with knowledge, memories, resistances, and collective aspirations.