Purpose This paper examines how artificial intelligence (AI) can transform sustainability management in agri-food supply chains by overcoming the limitations of intuition-based and linear decision-making approaches. Design/methodology/approach A qualitative and exploratory study was conducted by reviewing literature and conducting 15 semi-structured interviews with farmers, processors, distributors, supply chain managers and policy experts. A thematic analysis was applied to triangulate conceptual and practitioner insights. Findings Traditional agri-food supply chains are hindered by fragmented data, reactive strategies and limited integration of sustainability metrics. Adoption of AI applications enhances decision-making across environmental, economic and social dimensions for crop selection, production planning, quality control, marketing and distribution. However, this adoption is often constrained by affordability, digital literacy, infrastructure gaps and concerns over data sovereignty. Research limitations/implications While this study provides valuable insights into AI’s sustainability potential, further empirical research is required to deepen understanding and refine its applications and their consequences over a period of time. Originality/value The study positions AI as a cognitive partner in strategic decision-making within the agri supply chains; it offers a conceptual framework that integrates efficiency, equity and resilience. Particularly, it contributes to aligning agri-food systems with sustainability goals and highlights differentiated adoption pathways for multiple stakeholders.
S. Gupta (2026) studied this question.