Artificial intelligence (AI) has the potential to revolutionise agriculture more than any other sector, according to a leading expert.
Scott Angle, senior vice president of the University of Florida’s Institute of Food and Agricultural Sciences said AI is not only essential to meet global food demand by 2050, but uniquely suited to tackle farming’s most pressing challenges.
Writing in Robotics in Business, Dr Angle said that unlike the relatively controlled environment of a factory, agriculture is ‘teeming with variables’, from weather extremes and soil variability to pests, diseases and market volatility. Yet it is precisely this complexity that makes AI so valuable.
“AI is the Swiss Army knife of technologies. Literally every aspect of farming can be improved with adoption of AI-driven innovation,” he said.
One of the most immediate applications for producers is in plant breeding. AI systems can rapidly analyse large datasets to identify beneficial genetic combinations, accelerating the development of new varieties that are better suited to changing climates and resistant to emerging diseases.
In the US, AI has been used to develop citrus varieties resistant to greening disease, a problem that had slashed Florida’s production by 90% over two decades.
Autonomous machinery is another area with significant potential for cost savings and efficiency gains, he said.
Traditional tractors can cost upwards of half a million dollars, but AI-powered drones and robotic vehicles are emerging that may cost only $50,000 and operate 24/7 with minimal supervision. These systems reduce labour costs and allow for more timely field operations.
Crop protection is also benefiting from AI innovation, with new robotic platforms being trained to identify and target pests without the need for chemical applications. One such prototype is being developed to release predatory mites into strawberry fields, providing a ‘sprayless’ form of biological control.
Weather and pest simulations
On the decision-making side, AI-driven ‘digital twinning’ of farms, which involves creating virtual models based on real-time sensor data, enables producers to simulate weather events, pest outbreaks or input changes before implementing them in the field.
This allows farmers to optimise irrigation, fertilisation, and crop rotations with precision that wasn’t previously possible.
Marketing is another area where AI is closing the gap between small and large operations, Dr Angle added.
“Midsize farmers will have the ability to utilise sophisticated market analysis, thereby levelling the playing field with larger producers,” he wrote. This could help farmers better time sales and manage price volatility in a way traditionally reserved for large agribusinesses.
For producers, Dr Angle said the key takeaway is that AI is becoming accessible and practical, and not just the domain of universities or multinationals.
The next wave of agricultural tools won’t necessarily look like big machines, but rather algorithms and apps that help growers make smarter, faster decisions.
