Agriculture is facing a historic labor shortage at the same time artificial intelligence (AI) is reshaping how the world operates. Some fear AI adoption will result in job loss and businesses being left behind due to rapidly evolving technology. Others say AI is the digital farmhand agriculture needs right now to handle repetitive data tasks while humans focus on high-value animal husbandry or field work.
Either way, one thing is true – AI is not going anywhere.
“Whether AI replaces jobs or not depends on how the industry chooses to use it,” says Angel Andaya, manager of digital solutions for Silver Support, a managed development center supporting operations, finance, digital solutions, information technology and automation services.
If AI is seen purely as a replacement, she says that is likely the direction it will take. But it could also become a powerful tool to help farm operations thrive despite labor challenges.
The “Why Now” of AI: Accessibility and Adoption
While AI has existed for years (think Netflix recommendations and GPS), the launch of ChatGPT marked a paradigm shift that made the technology conversational and accessible to everyone, says Tracy Soper, senior director of data excellence at Keystone Cooperative.
“At 100 million [users] in two months, ChatGPT’s growth is unheard of – nothing has grown that fast,” Soper said at the National Pedigreed Livestock Council’s annual meeting. “Why? Because it was conversational and easy to access. It was something all of us could touch and could relate to, like, ‘Oh, this is a thing. It makes my life easier.’”
In the past, technology adoption took years. Now, it happens in months, creating a sense of “AI hysteria” and a need for clear strategy, he adds.
Problem First, People Always
Rather than viewing AI as a replacement for human expertise, it should be viewed as an amplification tool, he says. The strategy is to avoid expensive shelfware by starting with specific business problems.
“It can do a lot of things, but how are we going to use it?” Soper asks. “For us at Keystone, AI is not about replacing people; it’s making people better.”
Years ago, Soper says his job was to look over all things related to information technology (IT). Today that looks like AI and automation solutions as the cooperative’s scale has grown.
“For us, it’s starting very specifically with what problem we’re trying to solve today and then asking, ‘Why can’t we solve it with what we’ve got?’” he says.
Keystone takes a four-step approach:
1. Start with the problem, not the technology.
“AI only creates value when it’s solving a real business challenge. Companies that buy a tool, hand it to IT and expect magic end up with expensive shelfware,” Soper says.
2. Data readiness before algorithms.
“Any insight is only as good as the data feeding it,” he says. “We invested significant time building a modern data foundation before ever pursuing AI.”
3. Amplify expertise – don’t replace it.
“AI is not replacing agronomists, breed managers or the people closest to the animals. It’s amplifying their experience and sharpening their decision timing,” Soper explains.
4. Your data is the competitive edge.
“The competitive gap will be built on data readiness as much as algorithms,” he says.
In the future, Keystone is working actively in predictive machine learning and generative AI, using them to improve decision timing, streamline operations and better serve the producers who depend on the cooperative.
Shorten Time-Consuming Tasks
AI helps experts ask better questions sooner, Soper says. With data flowing more freely across the value chain, he believes there is great opportunity where AI and animal data converge.
For example, computer vision for body condition scoring, lameness detection and welfare monitoring is moving from research into practice in many barns. He’s also excited about how AI-assisted genomic prediction and health monitoring are advancing across species and can help make progress more quickly.
Andaya encourages farmers to think about the daily realities on the farm. What tasks are essential, but time consuming and repetitive?
“Even small improvements in how they are managed can free up valuable time and improve decision-making on the ground,” Andaya says.
If these processes are supported through AI, she believes it will enable farmers and their employees to focus more on animal welfare, planning and improving overall farm productivity.
“In this sense, AI is less about replacement and more about giving farmers and livestock teams the space to focus on what truly matters,” she says.
4 Tips for Successful AI Implementation
Agriculture and livestock operations are full of valuable data from daily logs to finances, Andaya explains.
“What’s changing is how effectively this information can be used,” she says.
Soper says Keystone has learned four important lessons in their journey to use AI more efficiently.
1. Data quality is everything.
Start with the data you own. Then budget time for discovery and cleanup.
2. Build for the people doing the work.
The tool needs to make someone’s job easier or it won’t get used. AI should amplify good discipline.
3. Scope tight, prove value first.
Prove it works before you scale. The business has to own the problem – IT enables, but stakeholders drive adoption and define success.
4. Governance can’t wait.
Policies around approved tools, data and data protection need to exist before people experiment. Once people start using AI on their own, it’s harder to rein in.
