Will artificial intelligence transform agriculture, or is it simply another tool in the producer’s toolbox?
That question sparked a lively and thought-provoking discussion during the Technology Panel: AI in AgTech, Where Will It Take Us? at WagyuEdge’27, where industry innovators examined the opportunities, challenges and practical realities of AI adoption across the beef supply chain.
Chaired by Charlie Perry, the panel brought together technology leaders including Sid Goutam, Gallgher, Davide Defendi, FarmBot Dan Garrick, Helical and John Hill, Land Watch to discuss how artificial intelligence is reshaping agriculture and where the industry may be headed next.
While the conversation explored some of AI’s most exciting possibilities, a clear theme emerged throughout the discussion: technology must solve real-world problems, not create new ones.
Cutting Through the Hype
Opening the session, Charlie Perry challenged the panel to consider whether some AI applications risk becoming solutions in search of a problem.
As AI continues to dominate headlines and investment conversations, Charlie encouraged delegates to focus on practical applications that deliver measurable value to producers.
That sentiment resonated strongly with the panel, which largely agreed that successful technology adoption depends on delivering tangible outcomes that improve efficiency, profitability or decision-making on-farm.
Technology Must Be Understandable
For John Hill, whose family business Land Watch develops technology solutions for agriculture, one of the biggest challenges is not building the technology itself, but helping producers understand its value.
John described his role as “chief storyteller”, explaining that effective communication is often what enables innovative technologies to move from concept to practical adoption.
“The storytelling side of it is so important,” he said. “A lot of it can end up in the too-hard basket, even when the technology is solving a very real problem.”
He argued that bridging the gap between technical development and practical application will remain critical as AI tools become increasingly sophisticated.
AI as an Accelerator, Not a Replacement
Dan Garrick of Helical shared how AI is already helping accelerate software development and innovation within the genetics sector.
According to Dan, artificial intelligence has significantly increased the productivity of software teams, making it possible to rapidly prototype new tools and features that support producers and breed societies.
However, he cautioned against overestimating AI’s current capabilities.
“One of the risks of AI is that it can very confidently tell you something that is completely wrong,” Dan said, highlighting the importance of human oversight and critical thinking.
That concern was echoed by several panellists, who emphasised that AI remains a powerful assistant rather than a replacement for expertise.
The Human Element Remains Essential
A recurring topic throughout the session was whether AI could ever replace the instincts and experience of skilled producers.
For Davide Defendi, the answer was a firm no.
David argued that no amount of technology can replicate the knowledge that comes from living and working within a production system every day.
“A farmer with AI will always outperform someone with AI who has no understanding of the farm,” he said.
Instead, he described AI as a democratised tool that can enhance decision-making but cannot replace local knowledge, intuition and experience.
The panel generally agreed that future success will likely come from combining technology with practical expertise rather than viewing them as competing alternatives
AI Agents and Automation Arrive on Farm
One of the most practical examples discussed came from Sid Goutam, who described how AI agents are already being used to streamline customer support and operational processes.
These specialised AI systems can be trained to perform specific tasks, such as diagnosing equipment problems, assisting customers with troubleshooting or managing warranty claims.
By automating repetitive processes, businesses can improve responsiveness while allowing staff to focus on higher-value tasks.
Sid noted that advances in edge computing and localised AI processing may soon allow many of these capabilities to operate without constant internet connectivity, addressing one of agriculture’s long-standing technological challenges.
Virtual Fencing and Autonomous Management
The panel also explored how AI could reshape livestock management systems.
Sid highlighted ongoing work in virtual fencing and autonomous livestock movement, where AI systems may eventually optimise grazing patterns, pasture utilisation and animal performance simultaneously.
By integrating information such as pasture availability, animal performance and target production outcomes, future systems may be capable of recommending or even automating grazing decisions.
While still emerging, these technologies demonstrate how AI could help producers manage increasingly complex production systems more efficiently.
Agriculture’s Data Revolution
Several panellists pointed to the enormous growth in available data as one of the most significant opportunities for the industry.
Dan highlighted the role AI will play in processing large volumes of information collected from wearable devices, electronic identification systems, cameras, genomic testing and other technologies.
Rather than replacing traditional measurements, AI may allow producers to capture vastly more information than would be possible through manual recording alone.
Potential applications include automated structural assessment, consumer preference analysis, behavioural monitoring and new genetic traits that have previously been difficult or impossible to measure.
Adoption Will Reward the Prepared
The panel agreed that AI adoption across agriculture remains in its early stages, but producers who ignore the technology entirely risk being left behind.
Drawing on the famous Moneyball example from baseball, David argued that early adopters often gain competitive advantages, but those advantages eventually become industry standards.
“You will have to adopt it,” he said. “The key is identifying where the technology provides real value and implementing it in ways that improve your business.”
At the same time, panellists warned against chasing every new technological trend without first identifying a clear return on investment.
A Future Built on Practical Outcomes
Despite differing perspectives on the pace and impact of AI adoption, the panel shared a common belief that technology should ultimately make farming easier, more efficient and more profitable.
As Charlie concluded, food production remains essential, and agriculture is uniquely positioned to benefit from technological advances without losing the importance of human judgement and experience.
For the Wagyu sector, the discussion painted a picture of a future where artificial intelligence supports rather than replaces producers, empowering them with better information, stronger decision-making tools and new opportunities to improve productivity across the supply chain.
The message from WagyuEdge’27 was clear: the AI revolution is coming, but its success will depend not on the technology itself, but on how effectively producers use it.