Increased use of data from smart farming technologies presents an opportunity for farmers to better understand their farm systems, and thereby improve outcomes for productivity, sustainability, and animal care. A research gap exists regarding the impact of data-driven smart farming on the relationship between advisors and farmers, and advisors and farm data/technology. Therefore, we asked: how are farmers and advisors interacting with data-driven smart farming, and what are the implications for farm advisor capability and roles in a future where farmers use more data-driven smart farming? We studied advisory roles, advisor-farmer interactions, and new technologies in the context of three case studies: i) automated cow body condition scoring in New Zealand; ii) precision grazing management in New Zealand; and iii) the Soil Water Outlook tool in the Australian grains and lamb sectors. We propose a conceptual framework involving on-farm adaptation, learning, capability development and organizational roles. The findings show that smart technologies exhibit potentially disruptive features for farm management, necessitating greater input from a farmer’s advisory network to facilitate optimal farm system adaptation. This has implications for the nature of the advisory relationship, where advisory capabilities evolve to include skills on determining technology value propositions alongside farmers and new skills are built for linking data to better decision-making on farm. This paper contributes to improved understanding of how back-office advisory roles may move from information gathering, to remote data interpretation due to data-driven smart farming. We identify the advisor’s role in acting as a sensemaker in the smart farming innovation system, rather than a promoter or barrier to technology uptake. Further adaptation of advisory practices is required to enable greater value from data-driven smart farming to be captured by farmers.

越来越多地使用来自智能农业技术的数据，为农民提供了一个机会，使他们可以更好地了解自己的农场系统，从而提高生产力，可持续性和动物保健的产出。关于数据驱动的智能农业对顾问与农民之间以及顾问与农场数据/技术之间关系的影响，存在研究空白。因此，我们问：农民和顾问如何与数据驱动的智能农业互动，以及在未来农民使用更多数据驱动的智能农业的情况下，对农场顾问的能力和角色有何影响？在以下三个案例研究的背景下，我们研究了咨询角色，咨询者与农民的互动以及新技术：i）在新西兰进行自动牛体状况评分；ii）新西兰的精确放牧管理；iii）澳大利亚谷物和羊肉部门的“土壤水前景”工具。我们提出了一个概念框架，涉及农场适应，学习，能力发展和组织角色。研究结果表明，智能技术展现出对农场管理的潜在破坏性特征，因此需要来自农民咨询网络的更多投入以促进最佳农场系统适应。这对咨询关系的性质产生了影响，咨询能力不断发展，包括与农民一起确定技术价值主张的技能，并且建立了新的技能来将数据链接到更好的农场决策上。本文有助于更好地理解后台咨询顾问角色如何由于数据驱动的智能农业而从信息收集转移到远程数据解释。我们确定顾问在智能农业创新系统中扮演感官的角色，而不是技术吸收的推动者或障碍。需要进一步调整咨询实践，以使农民从数据驱动的智能农业中获得更大的价值。