Australian farmers and researchers are slowly adopting AI for farming practices. Researchers and farmers in Australia have been testing various methods of using AI in agriculture to monitor pasture growth and identify crop diseases. They are also testing AI-based software that allows them to collect data on their farms and identify issues before they become serious. Below are three recent examples of how artificial intelligence in agriculture is being explored in Australia.

How AI Is Helping Farmers Track Pasture Growth

April 2026

The assessment of the quantity of grass available for consumption by livestock can be difficult, particularly on extensive grazing properties. To facilitate the process of assessing pasture growth, CSIRO, Google Australia, and Meat & Livestock Australia collaborated to develop a worldwide competition centered around applying Artificial Intelligence (AI) to quantify the amount of grass growing in pastures.

The competition attracted approximately 14,000 entrants from 109 nations. Entrants developed artificial intelligence (AI) models that would be able to predict the quantity of pasture based upon analysis of photographic images.

The study demonstrated that artificial intelligence can assist in determining both the quantity and species of vegetation used as feed. Farmers would find it easier to develop a grazing rotation schedule, assess the health of their pastures, and evaluate if they have sufficient amounts of feed for their livestock.

AI Helps Detect Sugarcane Disease Before Symptoms Appear

February–March 2026

Researchers at James Cook University created Sugar-AI, which utilizes satellite imagery and machine learning to identify signs of ratoon stunting disease in sugarcane crops.

Farmers are faced with the challenge that the disease could reduce their crops’ yields without showing visible signs of the illness. Farmers typically will take a sample from the plants they suspect have the disease and then submit the sample to a laboratory to determine if there is indeed a presence of the disease.

Sugar-AI takes an alternative route to identify if there are any differences in the way sugar cane looks when it is healthy and when it has been infected with the disease. Initial studies have shown that the AI can accurately determine whether or not sugar cane is diseased with 86%-97% accuracy depending on what type of sugar cane is being analyzed.

The technology being used to develop this system is still being developed, however it may allow farmers to locate areas that require additional monitoring, and act upon those findings quickly.

Australian Farmers Put an AI Farm Assistant to the Test

September 2026

AI is already being used to help manage day-to-day operations at farms. An article in September reported on the use of Farm Assistant, an AI application that combines data from paddock sensors, weather service providers, livestock markets, and financial records for a farm in Australia.

Voice notes and photographs allow farmers to record all of their data in one location. This eliminates the necessity for farmers to consult multiple sources when searching for needed information. Farmers can now access the information they need through a single system.

Technology like this may provide some relief to farmers who need to handle both their livestock and crops while managing their money, making it possible to spend less time on routine tasks and improve day-to-day operations. These examples show how AI in farming may help with everyday tasks, from monitoring pastures to keeping farm records organised.

What Do These AI Developments Mean for Australian Farmers?

The new advances highlight how the technology can solve some of the challenges that farmers encounter. AI can help in the calculation of pasture growth, detection of crop disease, and arranging farm records to provide the farmer with more data to guide their decision-making.

But it’s not always easy to use these tools. Considerate farmers also need to take account of the benefit of the tool, its accuracy and whether it is suitable for their farm. What works on one farm may not work on another.

So for now, the key task will be to find practical examples of AI that will have a positive impact on day-to-day work on a farm. Whether it is timesaving, crop monitoring or reporting, the proof will be in the results.

FAQs

1. How is AI applied to Australian agriculture?

Australian farmers and scientists are using AI for pasture measurement, identifying crop disease, and managing farm records. These are practical examples of artificial intelligence in agriculture that can support routine decision-making, although the application of AI will vary depending on the farm system and the technology.

2. Can AI help farmers identify diseases in their crops?

Yes, to grow healthy crops, it’s important to recognise the early signs of crop disease. Smart tools like Sugar-AI are being developed to help identify ratoon stunting disease in sugarcane, for example. These can help farmers determine which areas are worth closer investigation.

3. How will AI provide a helping hand to livestock farmers?

AI can assist livestock farmers with estimating grass availability in grazing fields. This can also facilitate forage planning, control of grazing rotations, and guide decisions regarding the timing of leaving a pasture.

4. Should all farms in Australia have AI?

Not necessarily. The price of the equipment, internet access, your farm’s size and where you’re located in the country can influence how practical an AI tool will be. Farmers need to weigh their needs before investing in new technology.

5. Will AI eventually take over the farmers’ jobs?

However, AI is more likely to be a help to a farmer than to replace one altogether. Farmers will be able to use the technology to make monitoring their crops, access information and collate data much easier; but farming is more than a bunch of figures, so farm management is what we’re trying to make easier, not to remove the farm from them.