Published on the 22/09/2026 | Written by Heather Wright

Farmers on how AI is helping turn data into decisions…

“We’re getting down from a mob approach to a more individual animal approach. Instead of looking at 1,000 lambs in a mob, we’re now looking at 1,000 individual animals in that mob,” says Carey Pawson-Edwards, stock manager for Lone Star Farms, neatly summing up what’s happening across New Zealand agriculture – and the value of tech.

A decade ago farmers were weighing lambs by hand, estimating pasture growth by walking paddocks with plate meters and making decisions using averages. Today, AI systems, sensors, automated weighing, satellite data and digital farm platforms are turning every animal, paddock and hectare into a source of real-time intelligence – fundamentally changing how farms are run.

“Our biggest limiting factor was ourselves and how we thought traditionally about how we’ve done things in the past.”

“Technology and AI have given me more time to spend thinking about and deciding on those higher value decisions, working on the business rather than in the business doing stuff day to day,” Pawson-Edwards said at this week’s AWS Cloud and AI Day in Auckland.

Recent research by ANZ Bank has shown agritech could provide a $2.9 billion opportunity for farms, uplifting revenue by five percent and decreasing costs by five percent.

Its report highlighted better-connected information systems, more efficient use of inputs, targeted automation, smarter land-use decision and investment in tools that genuinely fit the farm system.

For many farmers, the issue isn’t lack of information. Instead, it’s information siloed across multiple systems, from accounting systems and production records, to environmental reporting tools, spreadsheets and advisers processes.

“Farmers have a wealth of data and what they’re looking for is not more data but interpretation and decision support in that space,” says Mark McAtamney, chief digital officer at farmer owned agricultural co-operative Ravensdown.

Pawson-Edwards, who says Lone Star is only at the beginning of its tech and AI work, says at last count the business had 32 applications or programs that were all ‘keeping data in their corners’. “We’re probably only using 10-20 percent of that data to make decisions. For us, it’s going to be unlocking all that data and putting it into a format that we can make a decision at our fingertips and not be waiting a month to process it all.”

McAtamney says one important area is collaboration across suppliers and producers to ensure the data captured on the farm is able to be taken advantage of. “We’re seeing a lot of improvement in the collaboration between those businesses that are supplying or producing product from farm”

For Cheyne Gillooly, CEO of New Zealand Young Farmers, the opportunity extends well beyond individual farms.

“We’ve got some of the best sheep genetics in the world, we’ve got some of the best dairy genetics in the world and we’ve got some of the best plant and varietal information and it’s sitting in IP on shelves. Previously we would have to have scientists and entrepreneurs trawl through that for years to try and find the next chemical or next compound.

“AI can do that for us now so rapidly, so the pace at which we’re going to be able to innovate and generate new products that come from the land means we can unlock value that’s been sitting there potentially for decades.”

He says we’re moving from a world where technology and value were driven by speed and pace of innovation to one driven by ‘something that is tangible, something that is focused on human health, longevity and wellbeing, land-based products with our genetics that sit on top of that’.

“New Zealand is sitting on a good mine. The value of that data that’s currently untapped – it’s the magic of AI.”

He believes we’re on the precipice of exciting times for agriculture and farming as AI makes knowledge ubiquitous.

Pawson-Edwards admits he was sceptical when new systems were introduced. “To start with, I didn’t believe this sort of stuff was possible,” he says. “We had these people come and tell us we can lift pasture growth by this, we can improve that.”

The farm began cautiously, fitting 500 Halter digital collars across a herd of 2,500 cattle. The results came quickly. “Within probably three weeks it had changed our whole concept of this can actually work and is going to be really powerful.”

The farm now has pasture covers straight to the phone daily, rather than waiting a month for the data previously collected through a full-day of towing a plate meter behind the quad bike.

Looking back, he says the biggest obstacle wasn’t technology.

“I think probably our biggest limiting factor was ourselves and how we though traditionally about how we’ve done things in the past.”

Trust remains central to adoption. Farmers want evidence that systems work, recommendations are accurate and the data reflects what they see on the ground.

McAtamney recalls occasions during prototyping of a Ravensdown system where machine generated recommendations appeared unusual during testing.

“We would see something really unusual come out on the recommendation,” he says. They’d put the farm map on the table in front of the farmer and tell them ‘we think this is an error’. Their response: ‘Oh no, absolutely not. That’s exactly how we treated that paddock last year.’

Those moments helped build confidence that the models were correctly identifying patterns experienced farmers already understood.

Andrew McLaren, VP product and engineering for Kiwi agritech Halter, says at least half of the features in Halter have been added thanks to input from farmers.

“Once they understand what it can do, they can see the tiers to the possibilities of the technology so there have been a lot of creative ideas over the years that have ended up in the product.”

For all the attention on AI, the technology’s success in agriculture may ultimately be measured by something much simpler: whether it helps farmers make better decisions. If that happens, New Zealand’s next competitive advantage won’t be bigger farms or more animals. It will be the ability to extract more value from every hectare, every paddock and every data point.