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Barriers to AI Adoption in Indian Agriculture: An Initial Inquiry

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  • Asaf Tzachor

    (University of Cambridge, UK)

Abstract

Greater adoption of artificial intelligence (AI) in Indian agriculture can contribute to regional and global food security. An examination of parameters that may prevent and postpone AI transfer, diffusion, and adoption is essential. However, little research on AI adoption barriers in Indian agriculture has been conducted. This paper attends to the gap. In order to recognize, categorize, and prioritize the most critical impediments to AI adoption in Indian agriculture, this paper draws on a participatory research design in which workshops were used as the main research methodology. Seven working groups of local experts identified five categories of constraints, covering 18 explicit adoption barriers. Two constraints in particular were recognized as most critical: lack of trust in technology among farmers and a language barrier compounded by high illiteracy rates and a digital divide. With an initial catalog of constraints, this paper aims to contribute to the actualization of AI in Indian agriculture and thereby to local and global food security.

Suggested Citation

  • Asaf Tzachor, 2021. "Barriers to AI Adoption in Indian Agriculture: An Initial Inquiry," International Journal of Innovation in the Digital Economy (IJIDE), IGI Global, vol. 12(3), pages 30-44, July.
    • Handle: RePEc:igg:jide00:v:12:y:2021:i:3:p:30-44
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    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJIDE.2021070103
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    Cited by:

    1. Catherine E. Sanders & Kennedy A. Mayfield-Smith & Alexa J. Lamm, 2021. "Exploring Twitter Discourse around the Use of Artificial Intelligence to Advance Agricultural Sustainability," Sustainability, MDPI, vol. 13(21), pages 1-14, October.

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