Data Analytics, Artificial Intelligence (AI) and Sustainable Agricultural Production for the International Market

Richard Fosu (), Nana Yaw Asabere, Ernest Winful, Frank Opuni Frimpong and Daniel Odoom
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Richard Fosu: Accra Technical University, Department of Accounting & Finance
Nana Yaw Asabere: Accra Technical University, Department of Computer Science
Ernest Winful: Accra Technical University, Department of Accounting & Finance
Frank Opuni Frimpong: Accra Technical University, Department of Marketing
Daniel Odoom: Accra Technical University, Department of Accounting & Finance

A chapter in Proceedings of the International Conference on Sustainable Business and Entrepreneurship (ICSBE 2025), 2025, pp 105-117 from Springer

Abstract: Abstract The increasing global demand for food, coupled with the challenges of climate change and resource limitations, necessitates innovative approaches for the agricultural value chain. Advances in data analytics and artificial intelligence (AI) offer transformative potential to optimise agricultural practices, enhance productivity, and reduce environmental impact. This paper aims to explore how data analytics and AI technologies can be integrated into sustainable agricultural production systems to efficiently meet international market demands. It investigates the role of these technologies in improving crop yield, resource use efficiency, and market responsiveness. By bridging cutting-edge technologies with agricultural sustainability, this research addresses critical gaps in the current value chain. It offers insights to stakeholders—farmers, policymakers, and agribusinesses—on how to leverage AI-driven data analytics to support global food security and sustainable trade. The study employs a qualitative case study from an identified farmers and exporters group in Ghana. Results indicate that AI-powered data analytics significantly enhance precision agriculture through optimised input application and real-time monitoring. These technologies contribute to reduced waste, higher crop resilience, and facilitating sustainable supply chains for better alignment with international market standards. This paper uniquely integrates agriculture and international market dynamics with sustainability and technology frameworks. This approach offers a comprehensive perspective on implementing analytics and AI in agriculture on the global scale. It highlights novel methodologies and practical implications that have been underexplored in existing literature.

Keywords: Data Analytics; Artificial Intelligence; Agricultural Sustainability; Precision Agriculture; International Market; Food Security; environmental impact (search for similar items in EconPapers)
Date: 2025
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DOI: 10.2991/978-94-6463-930-8_9

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