Artificial Intelligence in agriculture: capturing stakeholders’ perspectives with a Q methodological approach

Purpose This study explores how stakeholders perceive and evaluate Artificial Intelligence (AI) in sustainable agriculture. While AI is often promoted as a solution to food security and climate challenges, its adoption raises ethical, social, and institutional concerns that remain underexplored. Design/methodology/approach Using Q methodology, the study captures subjective viewpoints from 20 stakeholders, including farmers, nutritionists, journalists, and health professionals. A Q sample of 30 statements was ranked and analysed through inverted factor analysis, revealing four distinct perspectives: “The Concerned Skeptic”, “The Critical Adopter”, “The Responsible Environmentalist”, and “The Technological Optimist”. Despite differences, all groups expressed concern over the digital divide and access inequalities. Findings The findings challenge linear models of technology adoption and highlight the value of context-sensitive, inclusive governance. Originality/value By integrating the Social Construction of Technology framework and extended Technology Acceptance Models, the study contributes a structured and interpretive understanding of how artificial intelligence is socially constructed in agriculture, offering practical insights for more equitable and responsible innovation.