Analysis of challenges to implement artificial intelligence technologies in agriculture sector

Nitasha Hasteer (), Archit Mallik (), Deepesh Nigam (), Rahul Sindhwani () and Jean-Paul Belle ()
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Nitasha Hasteer: Amity University
Archit Mallik: Amity University
Deepesh Nigam: Amity University
Rahul Sindhwani: Birla Institute of Management Technology
Jean-Paul Belle: University of Cape Town

International Journal of System Assurance Engineering and Management, 2024, vol. 15, issue 5, No 18, 1860 pages

Abstract: Abstract Artificial Intelligence (AI) plays a vital role in the agriculture sector. Its use in the agriculture industry to improve farming practices has increased over time. The uniqueness of AI in agriculture is its potential to transform conventional agricultural practices, opening the doors to greater productivity, sustainability, and, ultimately, a more secure global food supply. However, there are obstacles that limit the application of AI in this industry. Through a well-organized literature review, the study identified nine barriers that hinder the implementation of AI. To finalize the barriers for further investigation, the Delphi approach was employed. The barriers were analysed through modified total interpretive structural modelling (m-TISM) technique and categorized into 4 clusters using the Matrice d’impacts croisés multiplication appliquée á un classment (MICMAC) analysis. Lack of skilled workforce and extreme climatic conditions are major driving barriers that prevent effective AI adoption. Based on the findings, the study puts forward three propositions. Timely action on the recommendation can help mitigate the concerns and benefit the stakeholders in the agriculture sector.

Keywords: AI; Machine learning; Barriers; Internet of Things; Gross domestic product (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s13198-023-02164-z

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