While AI and machine learning are widely recognised for their impact on finance, advertising, healthcare, and retail, their transformative power in agriculture is often overlooked.
The Australian agriculture industry makes up a critical part of the economy and employs over 300,000 people. However, it has traditionally been viewed as labour-intensive and dominated by a rural workforce with lifelong on-farm experience.
The advent of agtech is rapidly working to update this image. By harnessing AI and machine learning to improve efficiency, productivity and sustainability in farming, agriculture is drawing new talent from diversified backgrounds to the sector. This evolution not only enhances the attractiveness of agricultural pursuits but also fosters a more dynamic workforce, paving the way for further innovation and growth.
Innovation and the adoption of technology are closely correlated to improvements in farm productivity, generating significant gains for decades. Technology has the potential to reduce labour inputs, optimise the use of seed, fertiliser and chemicals, and maximise output through higher yield crops and improved livestock genetics.
The sector is also attracting increasing investment. Total Australian agricultural R&D funding in 2022-23 was $2.32 billion, split between the private and public sectors. This mix of public and private expenditure is important because it helps drive the delivery of both short-term applied research and long-term underlying research.
Agriculture’s embrace of cutting-edge technology has led to the creation of job titles that would have been alien concepts just five years ago, such as “Precision Farming Technician”, “Compliance Food Technologist” and “Agtech Solutions Architect” as well as numerous Research Scientist and Agronomist positions.
Until recently technology adoption in agriculture was centred around better equipment and farm machinery. Now, AI is starting to play a role. Machine learning, computer vision and data integration are being applied to problems that were previously addressed through manual processes or institutional knowledge. Autonomous vehicles and robots can more efficiently spray herbicides or mow fields, with data used to refine their operations through smart algorithms. Livestock health is also being monitored via wearable sensors, with data processing systems constantly tracking for disease. In short, sophisticated technology is allowing farm operators to make much more data-driven decisions, taking them beyond having to rely only on gut instinct or prior experience.
It is a new frontier that is not yet oversaturated and gives specialists the chance to solve entirely new problems while applying their skills to make a difference. This goes beyond making incremental improvements to mature processes, to significantly move the needle on previously insurmountable issues such as identifying the marbling potential of a specific animal while it is still alive. This amount of value that AI and machine learning can generate for agriculture is unparalleled.
Bringing AI to agriculture is not just about introducing new technologies. It is about marrying deep agricultural knowledge with revolutionary machine-learning techniques to transform farming. A blend of expertise is critical as successful innovation in agriculture requires a deep understanding of areas such as crop lifecycles and the intricacies of animal husbandry. Collaboration between experienced farmers and technologists is vital to bridging the divide between legacy agricultural practices and modern technological capabilities.
This collaboration is helping younger graduates, often raised in non-rural areas, to learn more about industries and practices that may have been outside their sphere, broadening their knowledge and understanding of one of the nation’s most critical industries.
Automation is also generating job opportunities that are increasingly attractive to technology graduates. These roles often offer remote work options, eliminating the need to reside rurally. Agtech positions also offer graduates the opportunity to explore work environments they may not have previously considered. While some may have reservations about roles in the red meat industry, particularly those involving abattoirs, the integration of AI provides an avenue to still contribute their skills and creativity to the sector.
Another appealing aspect for emerging tech professionals is the opportunity to contribute to Australia’s sustainability goals and address pressing environmental concerns, ranging from climate change and carbon emissions to water usage.
Agriculture is one of the highest-impact domains for addressing these global priorities and this means that people can apply their skills towards meaningful change. This is particularly attractive to younger demographics, with 69% of Gen Zs and 73% of millennials actively trying to minimise their impact on the environment.
Agriculture is no longer just a career path for those with a farming family background or plant sciences majors. Roles are rapidly emerging that fuse AI with agribusiness, eco-activism, data science, and beyond – encouraging a generation of brilliant minds to see agriculture as a critical frontier for technological innovation and environmental progress, tackling some of the most pressing challenges of our time.
Mia Atcheson is the head of research and development of software and machine learning at MEQ.
