Key points are not available for this paper at this time.
This paper presents a literature review and interview study exploring the opportunities and hurdles when implementing Artificial Intelligence (AI) in agricultural businesses. Three sectors in agriculture are scrutinized: arable farming, milk production and beef production. As a foundation for the project, a literature review revises former research on smart farming. Thereafter, an interview study with 21 respondents both explores the susceptibility and maturity of smart farming technologies and provides technical depth to three chosen applications of AI in agriculture. Although the focus of the study is on the Swedish context, the findings can be generalized to the European agricultural sector and even world-wide. Findings of the study include a diverse set of aspects that both enable and obstruct the transition. Main identified opportunities are the importance smart farming has on the strategic agendas of several industry stakeholders, the general trend towards software technology as a service through shared machinery, the vast amount of existing data, and the large interest from farmers towards new technology. Contrasting, the study identifies main hurdles as technical and legislative challenges to data ownership, potential cybersecurity threats, the need for a well-articulated business case, and the sometimes lacking technical knowledge within the sector. The paper concludes that the macro trend points towards a smart farming transition but that the speed of the transformation will depend on the resolutions for the identified obstacles.
Jerhamre et al. (Thu,) studied this question.