From Aridity To Agility: AI-Driven Organisational Diagnostics For Scaling Controlled Environment Agribusinesses

Abstract

Agriculture and agribusiness had been using traditional methods till recently. The developments regarding AI applications in agriculture prompted many of them to adopt AI in various operations of agriculture and agribusiness. Considerable research has been done on this aspect. This qualitative PRISMA review aimed to evaluate the status of research in this respect. Google Scholar was used to identify the relevant papers, and the PRISMA process flow was used to screen and select the most appropriate papers based on some inclusion and exclusion criteria. This resulted in the final selection of 25 papers for this review. Considering that AI applications transform the current agricultural production systems into agile production systems, this review provided much information on how various AI and other technologies contribute to such a transformation. Production is the first stage of agribusiness.  At the local level, AI applications transform agriculture into sustainable food production. At the global level, it is concerned with global food availability and security. Apart from production, AI addresses product supply chains, post-harvest processing and marketing through market intelligence, to predict price and volume of arrivals in markets. AI chatbots recommend actions for agribusiness based on these predictions. All these apply to farmers who market their products themselves and large agribusiness firms. However, unless governments intervene with appropriate policies and strategies, a digital divide between the two will limit the access of AI technologies by small farmers. Some limitations of this review and some recommendations for research and practice have been given.