AI in Agriculture Market Size is Expanding Around USD 11,130 Million by 2032

Ottawa, Aug. 03, 2023 (GLOBE NEWSWIRE) -- The global artificial intelligence in agriculture market size will reach at USD 7,320 million in 2030. Artificial Intelligence (AI) in Agriculture refers to the integration of advanced computational technologies and algorithms to enhance various aspects of agricultural practices and farming operations. It involves the application of AI techniques, such as Machine Learning, Deep Learning, computer vision, Natural Language Processing (NLP), and robotics, to collect, analyze, and interpret data related to agriculture. AI in Agriculture enables farmers and agricultural stakeholders to make informed decisions, optimize resource utilization, and address agronomic challenges more effectively.

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By leveraging AI, farmers can gain valuable insights from vast amounts of data gathered from diverse sources, including weather patterns, soil conditions, crop health, historical farming data, and other relevant information. Some of the key applications of AI in Agriculture include precision farming, crop monitoring and management, predictive analytics, autonomous machinery and robotics, livestock monitoring, and supply chain management. These AI-powered solutions help improve productivity, reduce waste, minimize environmental impact, and promote sustainable agricultural practices.

Regional Insights

North America is expected to capture the largest market share over the forecast period. The region has been at the forefront of adopting precision farming practices, which heavily rely on AI technologies. Precision farming enables farmers to optimize resource usage, improve crop yields, and reduce environmental impact through data-driven decision-making. Moreover, Governments in North America have recognized the potential of AI in revolutionizing agriculture and have been supporting research, development, and implementation through various initiatives, grants, and partnerships. Furthermore, the region has a well-developed IT infrastructure and widespread internet connectivity creating a favorable environment for the adoption of AI technologies in agriculture. This facilitates the collection and transfer of data for analysis and decision-making. Thus, these factors support the market growth in the region.
The Asia Pacific is expected to grow at the fastest rate over the forecast period. The region has been increasingly adopting precision farming practices, which rely on AI technologies for data-driven decision-making and resource optimization. Precision farming enables farmers to tailor their agricultural practices to specific conditions and achieve higher productivity. Additionally, countries in the Asia Pacific have been investing in the development of AI-driven agricultural robotics and autonomous machinery. These technologies help address labor shortages, reduce human-intensive tasks, and improve overall farm efficiency. Thereby, driving the market expansion in the region.

Report Highlights

• By component, the software segment is estimated to hold the largest share of the market throughout the forecast period. The farmer can remotely monitor various farm areas by installing sophisticated software in sensors, cameras, and other surveillance devices that are installed at specific positions throughout the farm.
• By technology, the predictive analysis segment is expected to grow at a significant pace during the forecast period. By identifying patterns and trends, the models of predictive analysis technology can provide accurate predictions of crop yields for the upcoming seasons. This information helps farmers plan their resources, optimize input usage, and estimate potential revenue.
• By application, the drone analytics segment is expected to grow at the notable rate over the analysis period. Drone analytics in agriculture is a powerful application of drone technology combined with data analytics to optimize farming practices, enhance crop monitoring, and improve overall agricultural efficiency. Drones equipped with various sensors and cameras are deployed over farmlands to collect high-resolution imagery, multispectral data, and other relevant information. This data is then processed and analyzed using advanced data analytics techniques, including Machine Learning (ML) and Deep Learning algorithms, to provide valuable insights to farmers and agricultural stakeholders. These elements promote the segment’s growth.
  
  

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Scope of this report

Market Dynamics

Driver

Increasing adoption of drones

Drone analytics and AI integration in agriculture have a huge potential to improve sustainability, save costs, and optimize agricultural operations. Farmers may make data-driven choices, optimize resource allocation, and increase production by using AI to evaluate data collected by drones. A drone's high-resolution cameras and sensors may also collect a ton of information on the crops, the soil, and the features of the field. Farmers may learn important information about crop health, nutritional levels, insect infestations, and other aspects affecting agricultural output by combining this data with AI-powered analytics. Thus, the growing adoption of drone analytics is expected to drive market growth over the projected period.

Restraint

Data privacy and lack of awareness

AI systems in agriculture collect and process sensitive data related to farming practices, crop yields, and financial information. Ensuring data privacy and protection from cybersecurity threats is vital to build trust and encourage data sharing among stakeholders. In addition, many farmers may not be aware of the potential benefits and applications of AI in agriculture. Raising awareness and educating farmers about the capabilities of AI technologies can promote their adoption and utilization. Thus, data privacy and lack of awareness is observed to hamper the market growth.

Opportunity

Rapid adoption of advanced technologies

The faster adoption of cutting-edge technologies, including GPS, variable rate technology, mapping software, and data management software, has greatly increased agricultural output. The use of mapping software has significantly improved the capability to estimate agricultural production and track crop health using satellite photos and other input data. The farmer is helped in determining how much pesticide and herbicide needs to be sprayed on crops by the quick use of several types of sensors to detect different soil and ambient variables including PH level, moisture, and nutrient level. In addition, the use of modern robotics like drones and UAVs with a penetration of artificial intelligence techniques helps with the collecting of crucial data on things like plant count, irrigation, spraying, and crop health. Currently, trackers are also used to follow livestock. The farmer's capacity to determine the different weather patterns, soil conditions, and other qualities and choose which crops are best suited for his farm would be substantially enhanced by the collection of data regarding so many critical elements in a single database. Thus, the rapid adoption of advanced technologies is expected to provide a lucrative opportunity for market growth over the analysis period.

Challenge

Data accessibility and quality  

AI algorithms rely heavily on large and diverse datasets to train and make accurate predictions. In some regions, access to reliable and extensive agricultural data can be limited. Additionally, ensuring the quality and accuracy of data is crucial for the effectiveness of AI solutions in agriculture. Thus, this is expected to act as a major challenge for the market growth during the forecast period.

Related Reports

• Fertilizer Market - The global fertilizer market was estimated at USD 207.93 billion in 2022 and it is expanding around USD 271.6 billion by 2030 with a CAGR of 3.4% from 2022 to 2030.
• Agricultural and Farm Machinery Market - The global agricultural and farm machinery market was valued at USD 184 billion in 2021 and it is expanding around USD 374 billion by 2030 with a CAGR of 8.2% from 2022 to 2030.
• Agricultural Drone Market - The global agricultural drone market was valued at USD 1.1 billion in 2022 and it is expanding around USD 7.19 billion by 2032 with a CAGR of 20.7% from 2023 to 2032.
• Regenerative Agriculture Market - The global regenerative agriculture market was valued at USD 975.20 million in 2022, and it is expanding around USD 4,290.92 million by 2032 with a CAGR of 15.97% from 2023 to 2032.

Recent Development

• In May 2022, JCA Industries was acquired by AGCO to expand its engineering and software development skills and quicken the creation of highly automated and autonomous machinery.
• In April 2023, to give farmers insights into their water usage, IBM and Texas A&M AgriLife worked together. These insights can increase agricultural output while minimizing financial and environmental costs. Liquid Prep, a technological solution that aids farmers in determining "when to water" in arid areas of the United States, will be implemented and expanded by Texas A&M AgriLife and IBM.
• In September 2022, AgroCares announced cooperation to include trinamiX's high-performance technology into their onsite nutrient analysis system, which is the next-generation nutrient scanner solution. TrinamiX is based on mobile NIR spectroscopy and combines reliable hardware with adaptable software to improve on-site decision-making for on-the-spot nutrition monitoring in a variety of sectors.
  
  

Market Segmentation
By Component

• Hardware
• Software
• Services
  
  

By Technology

• Machine Learning & Deep Learning
• Predictive Analytics
• Computer Vision
  
  

By Application

• Precision Farming
• Drone Analytics
• Agriculture Robots
• Livestock Monitoring
• Others
  
  

By Geography

• North America
• Europe
• Asia-Pacific
• Latin America
• Middle East and Africa
  
  

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