TECHNOLOGY 72 FEED & ADDITIVE MAGAZINE January 2026 needs, such as optimizing to more precise amino acid requirements to reduce over-formulation, feed manufacturers can improve feed conversion while lowering costs. These gains also support sustainability goals through appropriate ingredient usage, reduction of nutrient excretion and overall environmental impact.” Mealey points to the latest version of Datacor’s software, Ara Formulation: “Ara Formulation allows nutritionists to model these strategies confidently, balancing economic and environmental objectives while maintaining animal health and performance.” A LOOK TO THE FUTURE: WHERE WILL BIG DATA AND AI TAKE LIVESTOCK? Big data and AI have begun to radically transform decision-making processes in the livestock sector. In the future, it is assumed that nutrition, health management, and production planning will be based on real-time analysis and predictive models rather than historical performance data. AI-supported systems will enable the dynamic adjustment of rations by predicting nutrient needs at the individual animal level, while early detection of disease risks will prevent losses. At the same time, increasing feed conversion rates, optimizing resource use, and reducing the environmental footprint remain primary goals. There is a widespread view that this transformation will move livestock toward a more efficient, traceable, and sustainable production model. Armin Pearn from DDW shares his future predictions based on practical field experience: “We work with 2 of the 5 major feed companies. Given the size of these companies and their complex business structure, it took them some time to drive digital transformation and change throughout their organizations. After a cautious start, we have seen a massive increase in the use of dairy data services from feeding companies over the last few years. And we expect these companies to use this momentum to leverage the power of AI on the data infrastructure and digital culture they have created going forward. As more farms use digitized feeding equipment, our AI models will be able to have an increasing amount of context not only of a given farm (i.e. dry matter content, feed consumed) or feeding group level but going forward also increasingly on animal level. This will drive feed conversion optimization and productivity on farm and in turn make dairy farms ever more sustainable.” Ian Mealey from Datacor explains his expectations for the future: “The most successful feed businesses are those that place importance on forward Source: Freepik.com I Created by AI
RkJQdWJsaXNoZXIy MTUxNjkxNQ==