Leveraging artificial intelligence in agribusiness: a structured review of strategic management practices and future prospects
Abstract This paper presents a structured review of the applications of Artificial Intelligence (AI) in agribusiness, emphasizing its transformative impact on farming practices. By integrating AI technologies such as machine learning, robotics, and data analytics, AI enhances productivity, sustainab...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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Springer
2025-07-01
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| Series: | Discover Sustainability |
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| Online Access: | https://doi.org/10.1007/s43621-025-01260-3 |
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| _version_ | 1849238831025356800 |
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| author | Irshad Ahmad Bhat Syed Immamul Ansarullah Fearoz Ahmad Sheikh Amir Sagar Sidana Anurag Sinha Saifullah Khalid Ghulam Yazdani |
| author_facet | Irshad Ahmad Bhat Syed Immamul Ansarullah Fearoz Ahmad Sheikh Amir Sagar Sidana Anurag Sinha Saifullah Khalid Ghulam Yazdani |
| author_sort | Irshad Ahmad Bhat |
| collection | DOAJ |
| description | Abstract This paper presents a structured review of the applications of Artificial Intelligence (AI) in agribusiness, emphasizing its transformative impact on farming practices. By integrating AI technologies such as machine learning, robotics, and data analytics, AI enhances productivity, sustainability, and profitability in agriculture. The paper explores key AI-driven advancements in precision agriculture, resource management, and supply chain optimization, which allow for real-time monitoring and informed decision-making. Additionally, the research discusses the ethical challenges and barriers to AI adoption, particularly in smallholder farming and developing economies. It also identifies emerging trends, such as the integration of AI with blockchain and biotechnology, to further optimize agricultural processes. The paper concludes with recommendations for advancing AI adoption, addressing data privacy concerns, and fostering inclusive, sustainable farming practices to ensure long-term resilience and food security in the agricultural sector. |
| format | Article |
| id | doaj-art-2a28ddf4922e44198cfff1dc3e61580a |
| institution | Kabale University |
| issn | 2662-9984 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Springer |
| record_format | Article |
| series | Discover Sustainability |
| spelling | doaj-art-2a28ddf4922e44198cfff1dc3e61580a2025-08-20T04:01:24ZengSpringerDiscover Sustainability2662-99842025-07-016112010.1007/s43621-025-01260-3Leveraging artificial intelligence in agribusiness: a structured review of strategic management practices and future prospectsIrshad Ahmad Bhat0Syed Immamul Ansarullah1Fearoz Ahmad2Sheikh Amir3Sagar Sidana4Anurag Sinha5Saifullah Khalid6Ghulam Yazdani7Department of Management Studies, University of Kashmir, North CampusDepartment of Management Studies, University of Kashmir, North CampusDepartment of Management Studies, University of Kashmir, North CampusDepartment of Management Studies, University of Kashmir, North CampusMaharshi Dayanand UniversityTech School, Computer Science Department, ICFAI UniversityPrincipal Scientist, IBM Multi Activities Co LtdJamia Hamdard UniversityAbstract This paper presents a structured review of the applications of Artificial Intelligence (AI) in agribusiness, emphasizing its transformative impact on farming practices. By integrating AI technologies such as machine learning, robotics, and data analytics, AI enhances productivity, sustainability, and profitability in agriculture. The paper explores key AI-driven advancements in precision agriculture, resource management, and supply chain optimization, which allow for real-time monitoring and informed decision-making. Additionally, the research discusses the ethical challenges and barriers to AI adoption, particularly in smallholder farming and developing economies. It also identifies emerging trends, such as the integration of AI with blockchain and biotechnology, to further optimize agricultural processes. The paper concludes with recommendations for advancing AI adoption, addressing data privacy concerns, and fostering inclusive, sustainable farming practices to ensure long-term resilience and food security in the agricultural sector.https://doi.org/10.1007/s43621-025-01260-3Artificial intelligence (AI)AgribusinessPrecision agricultureMachine learningSustainabilityAutomation |
| spellingShingle | Irshad Ahmad Bhat Syed Immamul Ansarullah Fearoz Ahmad Sheikh Amir Sagar Sidana Anurag Sinha Saifullah Khalid Ghulam Yazdani Leveraging artificial intelligence in agribusiness: a structured review of strategic management practices and future prospects Discover Sustainability Artificial intelligence (AI) Agribusiness Precision agriculture Machine learning Sustainability Automation |
| title | Leveraging artificial intelligence in agribusiness: a structured review of strategic management practices and future prospects |
| title_full | Leveraging artificial intelligence in agribusiness: a structured review of strategic management practices and future prospects |
| title_fullStr | Leveraging artificial intelligence in agribusiness: a structured review of strategic management practices and future prospects |
| title_full_unstemmed | Leveraging artificial intelligence in agribusiness: a structured review of strategic management practices and future prospects |
| title_short | Leveraging artificial intelligence in agribusiness: a structured review of strategic management practices and future prospects |
| title_sort | leveraging artificial intelligence in agribusiness a structured review of strategic management practices and future prospects |
| topic | Artificial intelligence (AI) Agribusiness Precision agriculture Machine learning Sustainability Automation |
| url | https://doi.org/10.1007/s43621-025-01260-3 |
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