For over 50 years, animal nutritionists have shaped the backbone of modern pig farming. But today, that expertise is being put to the test. With artificial intelligence, precision feeding, and next-generation technology transforming how pig diets are formulated and delivered, the traditional nutritionist’s role is at a crossroads. As algorithms outpace intuition and machines take over routine tasks, what’s next for nutritionists in pig production?
Nutritionists have long functioned as the translator between biology and economics. Their task: optimise the diet of a pig to achieve the best feed conversion ratio (FCR), growth rate, carcass quality and overall profitability. Diets are optimised to meet the nutritional requirements for energy, amino acids, minerals and vitamins, while minimising the cost of production and waste.
Traditional nutritionists:
- Collect feed ingredient data and use values predicted by book values or lab testing;
- Use least-cost formulation software to balance diets according to the National Research Council (NRC) standards or company-specific nutrient matrices;
- Interpret results from feed trials or metabolic studies to refine nutrient recommendations;
- Work with vets, production managers and feed mill operators to address health challenges, growth performance targets or raw-material changes; and
- Monitor herd performance metrics through spreadsheets or farm management software.
Wet-chemistry labs, near-infrared (NIR) analysers, spreadsheets and linear programming models have been the “tools of the trade.” Human interpretation, however, grounded in years of experience, has been the critical differentiating factor. However, humans err, and the risks of misinterpretation, misattribution or simply mistakes are considerable. Even with guardrails to avoid accidents, the actual costs of imprecise formulations often go undetected in a system with a lot of noise and implicit variation.
Digital disruption of pig production
The last 5 years have unleashed a wave of digital transformation that is fundamentally altering how pigs are raised and fed. Smart barns can now capture a continuous stream of real-time data from sensors, cameras and Internet of Things (IoT) devices. These data sets – tracking feed intake, water use, temperature, pig weights, activity levels and emissions – have the potential to create models that outperform even the most seasoned nutritionist’s intuition.
Sensors (IoT)
Adoption of the IoT on pig farms has been slow. Led by MSD (Anteliq) and Nedap, IoT usage has been slowed by the perception that it is expensive and creates work in an era of chronic labour shortages on farms. Australian innovator Xsights.io may be about to change that with the innovation of having a light attached to the device, which makes it easy for managers to find sick and/or high or low temperature pigs, keep track of those that have been treated, manage sows and follow their progeny. This technology is arriving in Europe on the back of its widespread adoption in Asia and Latin America.
Precision feeding and AI
AI-driven precision feeders, such as Big Dutchman’s CallMatic or Fancom’s IntelliTek, use algorithms to deliver individualised rations to sows and automatically adjust feed composition and volume based on growth stage, body weight and even genetic line.
Sensor and vision technologies
Cameras powered by computer vision – Farmsee, Ro-Main, OptiFarm, Asimetrix’s PigVision, and ClicRweight – claim to detect pig weights, body condition and welfare indicators without any human input. Sensor adoption in feed silo management for feed inventory in the field and feedmill, has been much more rapid (e.g. Binsentry, Distynct)
Digital twins and simulation
Emerging platforms, such as Digital Pig Twin projects in Europe and North America, offer the potential to simulate entire production systems virtually, and eventually do so on an animal-by-animal basis. They allow producers to test “what-if” scenarios without risking real animals.
Cloud-based integration
Feed formulation software is moving from desktop to cloud. Connected platforms, such as Adifo’s Bestmix Cloud or Cargill’s Nutrition Cloud, integrate ingredient prices, supplier data, and on-farm performance metrics in real time. Data systems, such as Prairie Systems (Ever.Ag) and Every.Pig, provide valuable information to inform nutritional decision-making.
Digitalisation is reshaping feed production
Digital disruption is not confined to the farm. Feed mills are becoming autonomous operations. Smart batching systems and inline NIR analysis adjust mixing in real time to guarantee nutrient consistency. Blockchain-style traceability ensures ingredient authenticity and safety. AI optimises logistics, predicting when each barn will need its next feed delivery and automatically scheduling trucks. Integrated swine operations can deploy enterprise data platforms that unify genetics, health, feed and production. The nutritionist’s once-siloed domain is being absorbed into a data ecosystem where machine learning, not manual calculation, drives decision-making.
The impact on the role of the nutritionist
As algorithms evolve from assisting to autonomously managing diets, the traditional “feed formulator” function is shrinking. This does not mean nutritionists will vanish – but it does mean that their role will be reinvented.
- From formulation to data interpretation
- Nutrition is moving toward real-time adjustment based on real-time data from feed analysis, farm data and the processing plant. Statistical and coding literacy are the new core skills.
- From batch diets to adaptive feeding
Nutritional algorithms will replace the current age-based diets (starter, grower, finisher) and evolve in a continuous data-fuelled feedback loop.
- From ingredient knowledge to system integration
Tomorrow’s nutritionist must understand sensors, data pipelines and AI ethics as much as amino acids or mineral interactions.
- From consulting to oversight
AI will take over routine feed formulation, while nutritionists become auditors – monitoring outputs for biological plausibility, welfare implications and regulatory compliance.
Risks and opportunities of the ‘new nutritionist’
This transition brings both peril and promise.
- Risk of deskilling: As machine-learning models assume control, fewer young professionals may gain hands-on formulation experience;
- Dependence on proprietary algorithms: Feed companies using black-box AI systems may lose transparency, risking welfare or regulatory violations;
- Data fragmentation: Without standardised formats, integrating data from sensors, feed mills, and farm software remains a major barrier; and
- Ethical and environmental implications: Automated optimisation could inadvertently prioritise other metrics over welfare or sustainability.
Universities are beginning to respond. Programmes at Wageningen University & Research, Oklahoma State University and Nanjing Agricultural University are embedding AI and precision livestock modules into animal science degrees.
The opportunities are immense. Digital tools can drastically reduce over-formulation, cut feed costs by 3% to 5% and lower nitrogen and phosphorus emissions. Real-time detection of digestive disorders or feed contamination can prevent disease outbreaks. AI-enabled forecasting can stabilise supply chains and reduce price volatility.
The “demise” of the pig nutritionist is not an obituary – it’s a transformation. Digital disruption is stripping away repetitive formulation tasks but is amplifying strategic influence. Those who cling to the old model will fade; those who evolve into digital nutrition architects will thrive.
As algorithms learn to feed pigs more precisely than humans ever could, the future of pig nutrition will depend less on who writes the formula, and more on who designs the system that decides it.
