AI-driven sustainable agriculture in reducing environmental impact: the role of market-oriented strategies

Purpose – This study aims to examine how artificial intelligence (AI) driven sustainable agriculture practices contribute to environmental sustainability among farmers in Ghana. It also examines the mediating role of market-oriented strategies in this relationship. Design/methodology/approach – The research used a quantitative approach and used structural equation modeling to investigate the impact of AI adoption on reducing environmental impact, mediated by market orientation strategies. The data were collected from 211 individual farmers who actively use/adopted an AI in their farming. Findings – The study identifies that the adoption of AI technologies has a strong and significant impact on improving crop management, resource efficiency and reducing carbon footprint. However, the mediating effect of market-oriented strategies showed mixed results for access to market and price mechanisms. Research limitations/implications – While the study offers a valuable conceptual framework, its generalizability may be improved with a bigger sample. Future studies are encouraged to conduct the study in other jurisdictions to validate the proposed relationships. Originality/value – This study contributes to the literature by bridging the gap between AI technological innovations and market strategy within the sustainability discourse. This paper goes beyond the techno-centric approach to reducing environmental impact and presents a holistic model that emphasizes market-oriented strategies as a key enabler of Adopting AI in reducing environmental impact within the agriculture sector.