PurposeThis paper investigates the relationship between agricultural entrepreneurship (AE) and new technologies using academic and practitioners' perspectives to understand how new technologies such as artificial intelligence (AI), machine learning and augmented reality can promote agri-businesses.Design/methodology/approachThe paper adopts a content and thematic analysis of 325 academic sources extracted from the Scopus database and 683 patents retrieved from the European Patent Office (EPO) dataset. Additionally, the research applies the Kruskal–Wallis test as a non-parametric test for evaluating differences in the main concepts discussed in the two sources.FindingsThe academic and practitioners' debate highlights a trading zone among the two streams. patents' analysis from the EPO reveals four main common themes as a new business that benefits from AI in weather predictions, new smart and intelligent ways to monitor crops, new businesses that use clouds to control plant's humidity. The analysis of Scopus's sources demonstrates theoretical approaches related to the technology acceptance model (TAM) and practical strategies in terms of entrepreneurial skills to support the agricultural sector. However, barriers among the two streams of sources exist in innovation management and scale-up entrepreneurial initiatives.Research limitations/implicationsRegarding implications, the authors aim to connect academic and practitioners' views by understanding the new potential innovation applications and the connected new research avenues. Limitations might arise from the sources used to develop our analysis.Originality/valueThe paper is novel because it investigates the issues arising from the relationship between AE and new technologies by examining original validated patents released by practitioners and approved by the EPO, rather than reviewing blogs or the financial press. This leads to a holistic understanding of the impact of tangible practices among agricultural entrepreneurs. The results support the view that new trading zones and case studies are needed to highlight and show the positive impact of technologies in this field. The authors argue that practitioners require scholars to reduce the ambiguity between AE and its expected results, leading to investments to boost new agricultural business ideas.
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