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Amidst the rising issues of food security and climate change, the agricultural sector has started deploying artificial intelligence (AI) in business operations. While many potential AI benefits are anticipated, a comprehensive understanding of the objectives motivating AI adoption and its impacts is lacking. This research attempts to fill this gap by exploring the key themes related to the use of AI in agriculture through the lens of dynamic capabilities. Using centering resonance analysis, we conduct text mining of news articles from 2014-2019 in the regions of Asia, Africa, Europe, and North America to identify how AI is addressing significant farming challenges. Globally, the results suggest that AI is primarily being applied to increase productivity and efficiency and secondarily to address labor shortages and environmental sustainability concerns. At regional level, the results reflect active AI adoption in North America and Europe with increasing efforts in Asia and Africa.
Lakshmi et al. (Wed,) studied this question.