Apr 20, 2023

Lyon, FRANCE New York, April 20, 2023 (GLOBE NEWSWIRE) -- Reportlinker.com announces the release of the report "Global Artificial Intelligence in Agriculture Market Size, Share & Industry Trends Analysis Report By Technology, By Application, By Offering, By Regional Outlook and Forecast, 2022 - 2028" - https://www.reportlinker.com/p06449952/?utm_source=GNW Precision farming, drone analytics, agriculture robots, livestock monitoring, and labor management are just a few of the applications of AI in agriculture that strive to maximize crop production efficiency. Adoption of deep learning technology is boosting crop productivity, fueling the market’s expansion. Farming with artificial intelligence approaches results in higher productivity and yield. Because of this, agricultural firms embrace artificial intelligence technologies for solutions based on predictive analytics. AI-based tools and methods assist with pest management, healthier crop production, soil monitoring, and jobs related to agriculture throughout the entire supply chain. Furthermore, since it assists in the analysis of farm data, artificial intelligence is increasingly being utilized by agriculture businesses to enhance harvest quality and accuracy. The need for AI in the agriculture sector is driven by the world’s rapidly expanding population. In addition, the demand for a green revolution powered by artificial intelligence, the Internet of Things (IoT), and big data is driven by the scarcity of arable land and the requirement for greater food production for food security. Several aspects of the agriculture sector are catered by AI-enabled apps, including predictive and recommendation analytics, plant disease detection, pest infestation detection, and soil monitoring. Aside from that, automation in agriculture assists in allocating resources like water and fertilizer, choosing the best time to plant crops, and identifying weeds, which increases the demand for artificial intelligence technologies. Using previous long-term weather forecasts, production data, commodity pricing forecasts, and seed information, among other inputs, it also assists in recommending how many seeds should be sown. Several IT juggernauts and start-ups are developing IoT-enabled devices to implement AI applications for agriculture on a wide scale due to the numerous advantages of these applications. COVID-19 Impact Analysis Using remote sensing and farm management software technologies resulted in greater uptake after COVID-19. As a result, businesses have already started to put more of a focus on wireless platforms to enable in-the-moment decisions in areas like crop health monitoring, yield monitoring, irrigation scheduling, field mapping, and harvesting management. Also, due to the spread of the pandemic, people worldwide have become conscious of the quality of food they are consuming. This has made it even more crucial to keep track of the health of yields. As a result, the adoption of AI technologies in agriculture has surged, profiting the market. Market Growth Factors Growing acceptance of IoT driving market expansion Demand is mostly driven by the growing deployment of IoT. The demand for IoT in agriculture is rising due to the expanding usage of mobile devices and cloud computing, as well as the numerous advantages offered by IoT, including the capacity to manage massive amounts of structured and unstructured data. For example, IoT sensors are utilized in agricultural practices to give farmers crucial information regarding rainfall, soil nutrition, crop yields, and pest infestation, among other things. Such data provides accurate information that can be used to promote crop production and can be used to raise the caliber of both farming practices and agricultural output. These elements would support the growth of the regional market. Growing use of robotics in agriculture A key development in the market is the growing use of robotics in agriculture. Farming techniques are advancing in sophistication and modernity due to the rising use of technology in agriculture. The usage of agricultural robots is expanding globally due to the expanding world population, the scarcity of farm employees, and the automation of the agricultural sector. Agribusiness stakeholders are also largely focused on improving output productivity through innovative farming techniques and minimizing the overall carbon footprint. Thus, robotics businesses are providing services that are AI-equipped to function in them. Market Restraining Factors Less technical knowledge among farmers Precision agriculture is a type of farming that necessitates an in-depth understanding of technology. However, owing to a lack of awareness of the implementation of cutting-edge technology, a gap exists between the comprehension and deployment of precision farming principles. Despite governments and market partners worldwide undertaking projects to provide farmers with training & consulting services on precision farming techniques, a significant percentage of farmers remain inaccessible. So far, farmers in developing nations lack technological competence, providing a substantial challenge for market players. Technology Outlook Based on technology, the artificial intelligence in agriculture market is segmented into machine learning, computer vision and predictive analytics. The computer vision segment garnered a substantial revenue share in the artificial intelligence in agriculture market in 2021. The increased usage of computer vision algorithms in agricultural applications, including sorting the food per weight, color, size, and ripeness and recognizing flaws in agricultural goods, is attributed to this high growth rate. Offering Outlook On the basis of offering, the artificial intelligence in agriculture market is classified into hardware, software, AI-as-a-service and services. The hardware segment projected a prominent revenue share in the artificial intelligence in agriculture market in 2021. Modern devices combine strong multicore CPUs to solve the parallel processing issue. Graphics Processor Units (GPU) and Field-Processing Gate Arrays are the most widely utilized, specialized, and often available hardware in AI systems developed on workstations (FPGA). An image-processing GPU is a chip designed to speed up the processing of multidimensional data. Application Outlook By application, the artificial intelligence in agriculture market is bifurcated into precision farming, agriculture robots, livestock monitoring, drone analytics, labor management, and others. The drone analytics segment dominated the artificial intelligence in the agriculture market with maximum revenue share in 2021. This is primarily due to the rise in venture capital funding for drone development and the increased need for high-quality food crops to feed the expanding world population. Also, there is an increase in the use of commercial drones in key application areas such as precision agriculture. Regional Outlook Region wise, the artificial intelligence in agriculture market is analyzed across North America, Europe, Asia Pacific and LAMEA. In 2021, the North America region led the artificial intelligence in agriculture market by generating the highest revenue share. Large-scale agricultural players in North America are already adopting AI technology to greatly speed up and enhance the precision of their planting or crop management procedures. The market for AI in agriculture is anticipated to expand in this region due to the desire for cutting-edge agricultural solutions. The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include Deere & Company, IBM Corporation, Microsoft Corporation, Climate LLC (Bayer AG), Farmers Edge Inc, AgEagle Aerial Systems, Inc., Prospera Technologies, Inc. (Valmont Industries, Inc.), A.A.A Taranis Visual Ltd., CropIn Technology Solutions Private Limited, and Corteva, Inc. (Dow AgroSciences LLC) Scope of the Study