Key parameters to increase the adoption of AI in agricultural decision support

This research paper contributes to the field of the application of artificial intelligence (AI) in German viticulture. The research gap addressed in this paper is the lack of research on the adoption of AI-based decision support in viticultural businesses. Consequently, expert interviews were conducted, yielding a multifaceted understanding of winegrowers' attitudes towards AI. The generated insights provide five dimensions with 48 subcategories that can influence the adoption of an AI system into a winery. From these subcategories, 14 parameters can be derived within the viticultural company, as well as external pressures from the environment and the AI system itself. This work leads to two further findings, which can be promoted as follows: firstly, the dimension “Functional & Physical Design of AI” can be derived from the interviews; secondly, the deductively derived “Trust in AI” is confirmed as another dimension alongside the dimensions described by the underlying framework.