AI is creeping into dairy whether we call it that or not, and most of the noise you hear is either hype or horror stories. So, we brought the conversation into the room with our first live event at the UK Agri-Tech Centre and asked a more useful question: what can artificial intelligence and machine learning genuinely do for a working dairy farm today, and where do the risks begin?

We’re joined by Chris Knight from Agribot, Ian Garner from Antler Bio, and Mike Jones from the UK Agri-Tech Centre. Chris pulls the curtain back on the history of AI, why the core ideas are older than most people think, and why large language models feel revolutionary mainly because we can talk to them. Ian shares how AI can speed up development and knowledge work without becoming a source of truth, including building science-grounded recommendations with expert validation to avoid confident nonsense and hallucinated references.

Mike brings it back to the coalface with tools being tested on real farms: earlier lameness detection, consistent body condition scoring, sensors that flag cows needing attention, methane monitoring, and even birdsong analysis for biodiversity benchmarking. Along the way we tackle accuracy versus consistency, predictive tools, data integration across too many apps, trust and privacy, and the awkward question of who really owns farm data.

This podcast was recorded in front of an audience, and once our guests had made their initial presentations, they then took questions directly from those in attendance, asking real questions relevant to farms today! 

This was recorded in February 2026, and all information was correct at the time of recording. 

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