From Feed to Health

Monday, September 22, 2025

Update On: AI in the Pork Industry

Artificial Intelligence Tech Emerging Slowly in Pork Industry

By Lilian Schaer For Livestock Research Innovation Corporation

Artificial intelligence is a hot topic seemingly everywhere at the moment. It’s making inroads in many different sectors of the economy – agriculture among them.

It was the focus of a session at the Ontario Swine Conference this past winter, where speakers gave a glimpse into the future of what AI can or is offering the pork industry.

“There are a ton of different businesses and small start-ups out there working on AI, and over time, we will see the leaders rise to the top and see what will pay off for producers,” says Dr. Dalton Obermier, a researcher at Jyga Technologies and one of the session presenters. “The key to success will be the wrap-up: What will it take for products and companies to make it through the next few years and get into the market and pig barns?”

The main areas where AI technology is making inroads in pork production are animal health monitoring, feed optimization, breeding, animal monitoring and tracking, environmental management, supply chain and waste management.

How widespread is its use so far in the pork industry, though? Not as much as producers might think, believes Obermier, who says although the topic is heavily researched and making headlines, implementation is still in its infancy.

“I think it is very minimal on the commercial side right now from an AI and machine learning perspective. There is a lot of automation, but AI is still relatively novel, and it hasn’t taken off just yet,” he noted.

Technology adoption has been lagging on-farm over the last several years of tight margins in the pork industry, which makes investment into innovations a tough sell. As well, for AI to be useful, the knowledge behind the automated processes must be solid and verified before it can be deployed in commercial settings – which takes time to build up and test.

The three most prominent areas for commercial application are health monitoring, feed optimization and environmental management, he said, predicting that the others are likely to be more niche market focused.

AI for animal health

The subclinical detection of disease – identifying a problem before it’s visible – is very important as it lets producers be proactive with treatment. Ultimately, this not only reduces costs, but it can cut down on the overall impacts on the pigs and their health and welfare.

“We have data showing that if you get a one to two day jump on PRRS (porcine reproductive respiratory syndrome) or PED (porcine epidemic diarrhea) before they break, it will make a significant difference in the overall impact it will have on a herd – as well as neighbouring herds or others in the same production system,” he says.

An example of predictive monitoring would be a system that could automatically analyze things like environmental conditions, staffing rotations, delivery vehicle routes and more to alert producers to the potential of a disease problem. Currently, producers can manually monitor feed intake, for example, to look for animals that are off feed – a common sign that they may be getting sick.

Belgian-based SoundTalks uses AI to analyze pig coughing using in-barn microphones, which can help detect respiratory problems up to five days before symptoms are visible.

Although not directly linked to disease detection, SwineTech’s SmartGuard system uses AI to reduce piglet mortality by protecting them from crushing by sows. The system detects piglets’ distress calls, which trigger vibrations or sounds that will encourage a sow to stand up.

And Farm Health Guardian from Ontario has built an AI-based biosecurity platform for hog and poultry barns that uses real-time location and health data to track and prevent disease spread.

Smart feed optimization

Jyga is one company working on technology around precision feeding. Historically pigs have almost always been fed a single diet in groups, and some systems exist that allow segmenting pigs by genetics, parities, age, or body condition scoring to tailor their rations more specifically to their needs.

Research is underway to develop individual nutritional requirement needs for sows and grow finish pigs based on information like environmental conditions or previous feed intake. It’s the AI that analyzes the data and makes the recommendations that would allow for automatic adjustment of feed curves, he says.

“Our end goal is to deliver the right nutrients, to the right pig, at the right time. Not only will this improve performance and save on feed costs but also make us smarter in drawing upon fewer resources for each pig.” he explains.

Environmental management

Environmental management focuses on parameters like temperature, humidity and ventilation in the barn and can also be tied to animal health monitoring.

An AI-based system, for example, can make recommendations for automated vent or water management, which could reduce energy and water use as well as ensure a more consistent or optimized barn environment for the animals.

OptiFarm in the UK is one example of a company that uses AI software to integrate environmental and welfare data to optimize both barn conditions and animal health.

Better production outcomes

At the end of the day, believes Obermier, producers and those working on-farm need to know that AI-based tools will not replace their jobs.

Rather, the idea is to make work more efficient and to support decision-making that is more objective than subjective – all with the goal of boosting producer returns.

“No computer or AI system can replace knowledgeable, experienced farm staff and managers,” Obermier says.

“We still have to have people who love pigs and animal agriculture and caring for animals on the farm.” BP