Automation and Artificial Intelligence: Transforming to Future Dairy Farming

Abstract This study examines the role of automation and artificial intelligence (AI) in transforming modern dairy farming and its implications for productivity and employment. The primary objectives are to analyse the adoption of advanced technologies, evaluate their impact on farm efficiency, and assess changes in labour dynamics within the dairy sector. The study is based on a descriptive and analytical research design using secondary data collected from research articles, government reports, and international agricultural databases such as FAO and OECD. Qualitative analysis and comparative evaluation methods are used to interpret trends in technology adoption, productivity, and employment. The findings reveal that the adoption of technologies such as automated milking systems, robotic feeding, smart sensors, IoT devices, and AI-based analytics has significantly improved dairy farm productivity. Average milk production has increased from 20–25 litres per cow per day in traditional systems to 30–35 litres in automated systems. Automation has reduced manual labour requirements while enhancing early disease detection, animal health monitoring, and data-driven decision-making. However, employment trends indicate a gradual decline in low-skilled labour, accompanied by rising demand for technical and digital skills. The study concludes that while automation and AI contribute to higher efficiency, sustainability, and better farm management, they also create challenges such as high initial costs, skill gaps, and inequality between large and small farmers. Policy support, training, and digital infrastructure development are essential to ensure inclusive and balanced growth in the dairy sector.