About 25% of job roles in agriculture could be replaced by large language models, with another 20% facing significant disruption, the Institution of Agricultural Engineers (IAgrE) artificial intelligence (AI) conference heard.
Professor Simon Pearson, Lincoln University, who holds the IAgrE Award of Merit, presented research suggesting that while AI will heavily impact cognitive roles in farming, dexterous tasks remain relatively protected.
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The shift represents one of the most significant transformations agriculture has faced in generations.
"We are going to see major changes in agriculture over the next five years due to AI adoption," Prof Pearson told the 90 online delegates.
However, he said this transformation required farmers to be trained to trust AI systems and make informed decisions based on their recommendations.
The conference, which was chaired by Farmers Guardian editorial director Olivia Midgley and sought to assess how AI was already revolutionising agriculture, highlighted that the skill requirements for future farmers were changing dramatically.
Rather than replacing human judgment, AI should augment decision-making capabilities, according to speakers.
The challenge would lie in ensuring the next generation understands how to evaluate and trust AI-powered decision support systems effectively.
Conference president Dr Mark Moore said that while not everyone was clear on exactly what AI is, ‘I know it is here to say'.
And his message was clear. If agricultural engineers do not embrace AI, they will be left behind.
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The UK Government's support through the modern industrial strategy and advanced manufacturing sector plan positions AI and agri-tech as two of six priority industries.
The conference showcased real-world applications already transforming farming. Allan Kildeby, head of camera sensors at CLAAS, detailed AI systems which were evaluating silage quality, grain quality, and detecting Rumex weeds in grasslands.
The company has developed automated data pipelines, cloud-based training systems, and model libraries to accelerate AI deployment.
Fernando Auat Cheein, an international expert on robotics from Harper Adams University, highlighted the UK's strong competitive position in AI research but noted fewer patents compared to other countries.
He said the challenge laid not in innovation but in creating sustainable business models that make AI accessible and profitable for farmers.
The reusability of hardware emerged as a key advantage.
Speakers explained how the same camera systems can collect data for multiple applications - optimising combine performance while simultaneously generating weed population maps for targeted control. This approach reduces costs for both developers and farmers.
However, Jonathan Henry, managing director of Garford Farm Machinery, identified significant barriers, including finding people with the right skills, managing project scope, and ensuring AI systems remain rugged enough for real-world farming conditions.
He stressed that manual labour remained both a risk and a cost, making AI-driven solutions increasingly attractive despite implementation challenges.
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