American
International
University-
Bangladesh

Students & Supervisors

Abstract

Agribusiness is central to food security and economic growth, particularly in the developing world where smallholder farmers are the principal factors in agriculture. Smallholder farmers are, however, faced with problems of poor access to global markets, price volatility, and inefficient supply chain systems. The emergence of AI offers transformative opportunities for developing sustainable agribusiness models that directly integrate farmers into global value chains. With the use of AI for demand forecasting, supply chain optimization, crop monitoring, and market prediction, it is possible to link the local farmers with consumers worldwide. Objective • To create an AI-based sustainable agribusiness model to enhance farmers' access to global markets. • To identify the role of AI in supply chain transparency, fair pricing, and sustainability. • To examine how AI-based systems can enhance productivity, reduce post-harvest losses, and allocate resources effectively. This study adopts a mixed-methods design that combines qualitative and quantitative methods. Secondary data from international agribusiness reports, FAO databases, and AI application case studies complemented by primary surveys/interviews with farmers and agribusiness stakeholders. Machine Learning algorithms for demand forecasting and price forecasting, computer vision for crop quality inspection, and blockchain integration to track the supply chain. Simulation of an AI-powered digital platform connecting Bangladeshi farmers to regional and international markets. Model performance assessment against key benchmarks such as market access, farmer income levels, supply chain efficiency, and sustainability index. The research comes to discover that AI-driven agribusiness models pretty much remove market inefficiencies and provide farmers with real-time data on global demand and price trends. Early findings show a 20–25% boost in revenues for farmers using AI-based market forecasting and logistics optimization. Transparency in the supply chain is achieved by integrating blockchain with AI, thereby giving farmers, distributors, and foreign buyers confidence. Resource optimization also reduces waste and promotes sustainability within the agricultural sector. The study demonstrates that AI-driven sustainable agribusiness models are able to bridge the gap between export markets and smallholder farmers through connectivity enhancement, transparency, and efficiency. Not only do these models ensure food security, but they also economically empower rural communities and are consistent with the principles of sustainable development. Large-scale adoption, policy mainstreaming, and the question of deploying AI and raising the question of its ethical concerns are research areas of exploration.

Keywords

Publication Details

• Type of Publication:
• Conference Name: 7th International Conference on Integrated Sciences (ICIS 2025)
• Date of Conference: 25/10/2025 - 25/10/2025
• Venue: Eastern University Campus, Ashulia, Dhaka, Bangladesh
• Organizer: Eastern University, Bangladesh