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Artificial Intelligence in the Agri-Business Sector: Prioritizing the Barriers Through Application of Analytical Hierarchy Process (AHP)
Abstract
The agri-business sector stands at the nexus of global food production, supply chain management, and rural development, yet it grapples with multifaceted challenges. In response, artificial intelligence (AI) emerges as a transformative force; however, the adoption of AI in agriculture faces significant barriers, particularly in countries like India. This study systematically identifies and prioritizes these barriers using the Analytical Hierarchy Process (AHP) methodology. The results highlight the paramount importance of technological infrastructure, data accessibility, and skill development. Ethical considerations around safety and transparency, economic constraints, and social-cultural acceptance also emerge as critical factors. The study offers insights into the relative significance of each barrier, facilitating informed decision-making and targeted interventions. Ultimately, by addressing these barriers, stakeholders can unlock new opportunities for growth, sustainability, and food security, ensuring prosperity for agricultural communities in the digital age.
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