An artificial intelligence (AI)-readiness and adoption framework for AgriTech firms

Helmi Issa, Rachid Jabbouri and Mark Palmer

Technological Forecasting and Social Change, 2022, vol. 182, issue C

Abstract: With recent technological advancements, empowered by the self-learning capabilities of algorithms and increasing power of machine computation, artificial intelligence (AI)-driven technologies have become more salient for addressing and solving specific types of business problems. This saliency is no less important for firms operating in the agricultural technology (AgriTech) sector, where the impacts of AI-driven technologies and systems create new opportunities and challenges. We argue that with the unique characteristics of AI technologies and emerging challenges and aspirations of the AgriTech sector, there is a need to rethink traditional theories of technology adoption and readiness within AgriTech firms. In this paper, we develop an understanding of AI readiness and adoption through a fuller appreciation of micro- and meso-empirical data that delineates the determinants of AI readiness and uncovers a set of strategic components that can help AgriTech firms better manage the readiness process for AI adoption. To do this, we employ a mixed-methods approach and elicit data from 236 e-surveys and 25 interviews from an important conference in the AgriTech field. Our findings have implications for research and practice to understand AI technological readiness.

Keywords: Artificial intelligence; Agricultural technology; Readiness and adoption; Mixed- methods (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:182:y:2022:i:c:s0040162522003985

DOI: 10.1016/j.techfore.2022.121874

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