The market size of the Global Artificial Intelligence in Livestock Farming Market is predicted to show an 26.2% CAGR during the forecast period.
A large portion of livestock processes and steps are manual. By improving already-adopted Technology, AI may simplify even the most routine and challenging tasks. It can gather and analyze a lot of data on a digital platform, choose the best course of action, and even start that action when used in concert with other technologies. The primary market growth driving drivers will emerge as increasing globalization and an increase in the use of new cutting-edge Technology by the livestock industry. The market value will be further positively impacted by rising demand for high-quality livestock products, encouraging government programs and initiatives to promote advanced livestock tools and practices, and growing industrialization. The rising costs associated with conducting research and development projects and the increasing use of drones in livestock fields will further expand the market. Improvements in feed quality, computer-aided vision algorithms, livestock health monitoring, supply chain optimization, and real-time behaviour monitoring are among the application areas covered by AI technology. With AI's disruption of the livestock business, numerous start-up companies have entered the market and developed cutting-edge IoT sensors to address farmers' unmet demands.
However, a lack of technological know-how and knowledge will prevent the market from expanding. Technological difficulties, interoperability problems, and a lack of standardization will further slow the market's development pace. The developing economies' extensive technological restrictions and the significant expenses involved in precise field data gathering will make achieving the market development rate even more difficult.
The Artificial Intelligence in Livestock Farming Market is segmented on the basis of Component, Application, Type, Farm Size, and Technology. Based on the Component, the market is segmented as Solution/ Software/ App, IoT Sensors, and Services. Based on Application, the market is segmented as Real-Time Livestock Behavior Monitoring, Healthcare & Disease Monitoring, Livestock Feed & Water Monitoring, Livestock Control & Fencing Management, and Livestock Production Management. Based on Type, the market is segmented as Semi-Automatic and Fully-Automatic. Based on Farm Size, the market is segmented into Small and Medium-Sized Farms and Large Sized Farms. Based on Technology, the market is segmented into Computer Vision, Machine Learning, and Predictive Analysis.
Based on Components, the IoT sensors segment is accounted as a major contributor in the Artificial Intelligence in Livestock Farming Market.
The Internet of Things (IoT) sensors market will have the fastest growth with the greatest CAGR because of the increased requirement for sensors and intelligent devices in farm setups to reduce labour and manual maintenance costs. The segment's expansion is greatly influenced by farmers in developed regions being more knowledgeable about the sensors and gadgets that can track the feed levels and vital signs of the livestock on their farms. This has substantially contributed to the sensor sector's overall growth. In recent years, smaller sensors have been fast incorporated into gadgets, including wearables, smartphones, drones, and robotics, which is also assisting the market's expansion. The rapid adoption of the Internet of Things (IoT) by farmers and growers, the growing emphasis on livestock monitoring and disease detection, the high demand for fresh produce, population growth, the loss of arable land, the rapid adoption of aquaculture monitoring and feed optimization devices in developing countries and the strong government support for precision farming practices are some of the factors that are driving the growth of the IoT sensors segment.
Based on Technology, the computer vision segment is accounted as a significant contributor to Artificial Intelligence in Livestock Farming Market.
The market's most significant stakeholder will be computer vision. The use of computer vision for animal monitoring opens the door to non-intrusive livestock monitoring. Visual Artificial Intelligence (AI) is one of the most promising technologies to automate inspection and decrease expenses to survive under solid cost pressure and severe competition as a result of the growing demand for animal monitoring systems. This is motivated by things like managing animal comfort, managing reproduction, or early disease detection. It is now feasible to create autonomous computer vision systems for animal monitoring and observation that can match or even outperform human accuracy because of the quick advancements in machine learning.
The North America Artificial Intelligence in Livestock Farming Market in the region holds a significant revenue share.
North America will control a sizable portion of the market throughout the forecast period. With the expanding use of IoT and computer vision technologies in the livestock sector, the market will expand significantly during the anticipated period. The region's growing demand for hands-free cattle handling, rise in the prevalence of low-quality milk and dairy products, and improved awareness of the most recent technologies for managing farm animals may contribute to North America's market share dominance. Businesses like IBM Corporation and Raven Industries Inc. are increasingly collaborating with other firms to better their goods for the livestock sector. Additionally, through agreements with other major firms, a number of regional players offer services to local customers. In the Americas, significant players in livestock are already implementing AI technology to improve their management processes' effectiveness and precision dramatically.
Some of the major key players in the Artificial Intelligence in Livestock Farming Market are Connecterra, Rex, Cainthus, Vence, SmartShepherd, Quantified AG, AgriWebb, BovControl, BinSentry Inc, Faromatics, FarrPro, H2Oalert, Hencol, Jaguza Tech, Moonsyst, Roper, Simple Ag Solutions, SomaDetect, and SwineTech.