How agricultural advisers use artificial intelligence (AI) to support farmers: Evolving roles and collaboration in Australian digital agriculture

Artificial intelligence (AI) is becoming an increasingly important part of digital agriculture, enabling more timely and precise decision-making. Understanding how advisers use AI is important because they play a critical role in supporting innovation in farming, including by influencing how farmers interpret, trust and realise value from AI. Yet few empirical studies have examined how advisers use and respond to AI in practice, how AI reshapes their roles, capabilities and collaboration, or how they support farmers to engage with AI-enabled innovations. This project investigates these changes across Australian digital agriculture and considers their implications for irrigation and water management in the Murray-Darling Basin, particularly for viticulture, horticulture and cotton production.

About this project

Artificial intelligence (AI) is increasingly being integrated into digital agriculture, creating new possibilities for timely decision-making, data-driven insights and more precise agricultural management. AI-enabled technologies, such as machine learning, decision-support systems, large language models and computer vision tools, have the potential to support agricultural extension and advisory practice, including digital irrigation and water-management decision-making. However, research on agricultural AI has largely focused on technical applications such as weather forecasting, pest detection and crop monitoring. Few empirical studies have examined how advisers use and respond to AI in practice, how it affects their roles and capabilities, or what opportunities and challenges it creates for advisory services.

Agricultural advisers are important actors in digital agriculture because they translate complex information, technologies and data-driven insights into practical support for farmers. Their roles have expanded beyond technical advice on farm productivity to include environmental sustainability, climate adaptation and technology investment decisions. As AI becomes more embedded in agriculture, advisers may need new expertise both to support farmers engaging with AI-enabled innovations and to incorporate AI into their own advisory work.

This project also responds to the increasingly pluralistic and fragmented nature of agricultural extension and advisory systems. Advice is now provided by diverse actors, including extension officers, independent consultants, agronomists, technology suppliers, research institutions, agribusiness consultancies and start-ups. While this diversity broadens access to knowledge and expertise, it may also create information imbalances, constrain knowledge exchange and contribute to fragmented or contradictory advice for farmers. Existing research has focused primarily on how individual advisers adapt to digital agriculture, with less attention to collaboration, knowledge exchange and role coordination among different adviser types, particularly in AI-driven environments.

To address these gaps, the project will draw on the perspectives of advisers across Australia through semi-structured interviews and a national survey. It will examine how advisers engage with AI in practice, how their roles and capability needs are changing, how they support farmers to engage with AI-enabled innovations, and how different adviser types collaborate and exchange knowledge.

Expected Outcomes

The project will generate empirical evidence on how AI is changing agricultural advisory practice in Australia. By identifying how advisers use and respond to AI in their own work, the capabilities they need, and the forms of collaboration that support effective AI use, the research will inform professional development, advisory service design and coordination across advisory networks. These outcomes will help advisers use AI more effectively in their own practice and, in turn, strengthen their support for farmers engaging with AI-enabled technologies, particularly in irrigated industries across the Murray-Darling Basin, such as viticulture, horticulture and cotton production.