A Foresight Study of Artificial Intelligence in the Agriculture Sector in Malaysia - Rodzalan, Shazaitul Azreen; Ong, Guan Yin; Mohd Noor, Noor Nazihah (Journal of Critical Reviews, 2020)
Agriculture is one of important sector in Malaysia which contribute to the national GDP and provide employment for the society. Agriculture sector also has become the focus of the rural development programs. However, economic diversification has recently shifted the focus from agriculture to manufacturing and services sector. A comprehensive reform is needed by adopting smart farming to revitalize Malaysia’s agriculture sector. Therefore, the aim of the research is to identify the issues, drivers and future trends of Artificial Intelligence (AI) in the agriculture sector in Malaysia. This research used foresight tool such as STEEPV to identify the issues and drivers. Questionnaires were distributed to the respondents who were farmers in Johor. Based on the data collection, 150 out of 380 respondents had answered the questionnaire. The findings showed the technological factor has the highest frequency compare to other five factors. A total nine major issues and drivers were also identified. From the impact-uncertainty analysis, the top two drivers which were replacement of employees and productivity enhancement and optimize economic had chosen. The top two drivers were used to develop scenario analysis. The scenario analysis included market expand, shortage of manpower, wastage of resources and impede development. This research gives benefits to agriculture sector, farmers and the consumers. This research also gives a foresight of the trends that may happen in the future. This research can helps to increase the quality of life, develop technologies and innovation, growth of economic and environmental friendly.