The agri-food industry is in the midst of a massive crisis due to low economic growth and production. Recently, the adoption of several AI technologies has aided farmers in producing thousands, thereby reducing human intervention in food production. The components of artificial intelligence, which include learning, perception, problem solving, and reasoning, have aided the agri-food business industry in identifying sustainable models for crisis management. In this chapter, the author proposes a four-stage strategic roadmap for addressing the challenges associated with implementing artificial intelligence to manage crises in the agri-food business.
TopIntroduction
The implementation of AI technology within the agri-food industry is not a common element across the globe. Hence, the implementation of AI technology within the agri-food industry can be identified as an exception (Di Viao, 2020). However, implementing this advanced technology can be helpful for different tasks such as analysing the weather forecast, business analytics and establishing effective supply chain management (Ibáñez and Blázquez, 2021).
According to recent research, it can be understood that the use and popularity of AI within the Agri-food business has been increasing day by day as it has the potential to provide comparatively higher profitability (Maté-Sánchez-Val and Harris, 2018). AI can improve the overall accuracy and quality of the agricultural process of agri-food businesses (Rabadán et al., 2019). AI is helpful to detect and automate major crises in the agri-food business industry, including over-dependency on climate, rainfall, and the rampant usage of pesticides, which over time causes environmental degradation (Yadav, 2020).
The implementation of technology is not only sufficient in this industry. It is crucial to provide proper training to each handling the agricultural activities on a day-to-day basis. It is the most important challenge faced by the decision-makers of this industry as providing training to everyone is comparatively a time and cost taking approach. Therefore, it is essential to identify specific and simplified processes for training the individuals and discussing the importance of the system within this industry (Rabadán et al., 2019).