By Aidan Connolly, AgriTech Capital & Camila Ulloa, Purdue University
Pork production has always been a business of timing. Breeding schedules, feed deliveries, pig flow, ventilation adjustments and marketing decisions must all happen at the right moment. When those decisions are coordinated well, the system runs smoothly. When they are delayed or disconnected, small problems can quickly become expensive ones.
Today the pace of decision-making in pork production is accelerating. Labor shortages, volatile feed prices, disease pressures and unpredictable markets are forcing producers to operate with greater precision than ever before. Recent industry analyses also show that hog prices have experienced significant swings due to supply chain disruptions, disease outbreaks and export demand shifts. Artificial intelligence is emerging as a tool that can help producers turn operational data into faster and better decisions.
AI is often described as futuristic technology. In reality, it is simply a new way of using information. Modern pig farms already generate enormous amounts of operational data: feed intake, water consumption, barn temperatures, growth rates, mortality and processing weights. The challenge is not collecting the data; it is turning it into decisions quickly enough to matter.
Artificial intelligence helps solve that problem by identifying patterns across multiple data streams simultaneously. Instead of reviewing reports after problems occur, AI systems can detect early signals and recommend adjustments while outcomes are still manageable. For pork producers, the shift is subtle but important. Management moves from reacting to events toward anticipating them.
Why Pig Production Generates So Much Data
Modern swine production generates data at nearly every stage of the production cycle. Large production systems manage breeding farms, nurseries, finishing barns, feed mills and processing plants across multiple locations. Each stage produces its own set of measurements and records. Environmental controllers track temperature and ventilation inside barns. Feed systems record feed usage. Weigh scales monitor growth performance. Health treatments and vaccination programs add additional records, while processing plants provide feedback on carcass weight and yield. Individually, these datasets are useful. But they often remain isolated within separate software systems or management processes.
Nutrition, ventilation, breeding and marketing decisions all depend on different types of information. Yet these decisions influence one another across the production cycle, and the data needed to coordinate them is rarely analyzed together.
Rather than analyzing each issue separately, AI systems evaluate how multiple variables interact across the production system. In practice, this means artificial intelligence can help producers understand how:
- changes in feed formulation influence growth curves and marketing weights
- ventilation and temperature patterns affect feed intake and animal health
- ingredient variability impacts finishing performance
- health signals in barns influence downstream processing schedules
When these relationships become visible earlier, producers can adjust sooner.
From Observation to Prediction
Traditionally, good pig managers relied heavily on observation. Experienced producers could walk through a barn and quickly recognize when pigs were uncomfortable or when something in the environment was not quite right. Artificial intelligence does not replace this expertise. Instead, it extends it. Sensors track feed intake and water consumption continuously. Environmental systems monitor temperature and airflow. Cameras and sound sensors detect changes in activity levels or coughing patterns. When analyzed together, these signals provide a clearer picture of herd health and barn performance.
The result is earlier intervention. Health issues can be detected sooner, reducing treatment costs and mortality. Environmental adjustments can also be made earlier to prevent heat stress or growth setbacks. Predictive insights also improve planning, helping producers schedule marketings more accurately and coordinate better with processors. In this way, AI does not change the fundamentals of pig farming. It simply allows producers to see patterns sooner and respond faster.
The Bullet Train Moment for Pork Production
Transformational technologies rarely succeed on technology alone. They require changes in the systems around them. A useful comparison comes from transportation history. When Japan introduced the Shinkansen bullet train in the 1960s, the breakthrough was not simply building a faster train. The entire railway network had to be redesigned. Tracks were rebuilt, signaling systems upgraded and operating procedures rewritten. Without those changes, the train would never have achieved its famous speed.
In our recent white paper on AI in agri-food we describe how artificial intelligence presents a similar moment for agriculture. Installing AI software without adjusting how decisions are made is like placing a bullet train on old railway tracks. The technology may be powerful, but the surrounding system limits its impact. For pig producers, the key challenge is not simply adopting digital tools. It is reorganizing how information flows across the operation.
Turning Information Into Better Decisions
In a previous column in Farm Journal’s PORK titled “Smarter Pigs, Smarter Farms: How AI and ChatGPT Are Re-Wiring Swine Production,” I introduced the DRIVE framework as a practical guide for pork producers interested in experimenting with artificial intelligence. That article explains the steps in detail. The principle remains simple: artificial intelligence creates value when it helps producers connect information that already exists across barns, feed mills, health records and marketing plans.
The Next Stage of Pig Farming
The swine industry has repeatedly adapted to new technologies. Genetic improvements, precision feeding systems and modern ventilation controls have reshaped production over the past several decades. Artificial intelligence represents the next stage of that evolution. But the real transformation will not come from algorithms alone. It will come from producers who rethink how information moves through their operations and how decisions are made across breeding farms, nurseries and finishing barns.
In railways, the bullet train succeeded because the entire infrastructure evolved around it. In pork production, artificial intelligence offers a similar opportunity. The farms that move fastest will not simply install new software, they will redesign their decision systems so information works together across the entire operation. Because in modern pig farming, the ability to learn quickly may become just as important as the size of the herd.
Aidan Connolly, President, AgriTech Capital, is described by Forbes as ‘a food/feed/farm futurologist’ He is the author of the book ‘The Future of Agriculture’, now in 4 languages, and a recent white paper on AI in Agri-Food systems. Camila Ulloa is a market research analyst, with a master’s in agricultural economics from Purdue University. Her work combines industry analysis and applied research on innovation, sustainability, and emerging trends across agriculture and food systems.
