Artificial Intelligence (AI) in Agriculture Market Size, Trends, Share, Growth, and Opportunity Forecast, 2023 - 2030 Global Industry Analysis By Component (Hardware, Software, and Services), By Technology (Machine Learning, Computer Vision, Predictive Analytics), By Application (Livestock Monitoring, Precision Farming, Drone Analytics, Labor Management, Agriculture Robots, Weather Tracking, and Others), and By Geography (North America, Europe, Asia Pacific, South America, and Middle East & Africa)

The Global Artificial Intelligence (AI) in Agriculture Market was valued at USD 1,544.6 Million in 2022 and is anticipated to reach a value of USD 7,887.6 Million by 2030 expanding at a CAGR of 22.7% between 2023 and 2030.

Artificial intelligence (AI) is based on the principle that human intelligence, that a machine can easily mimic it and execute tasks from the simplest to more complex. Artificial intelligence in agriculture   plays a crucial role in solving the global food crisis and other agriculture problems. Artificial intelligence can be utilized to alleviate the global issue of food inequality. The integration of artificial intelligence in agriculture has the potential to transform food systems and help to address the global food crisis. It involves the use of advanced technologies such as machine learning, data analytics, and computer vision to automate farm and crop management. Artificial intelligence is transforming the agriculture field by analyzing data from various sources, enhancing efficiency, productivity, making data-driven decisions, and reducing environmental impact.  AI in agriculture offers several advantages to the farmers such as improving farm yields, grow more crops with fewer resources, best soil management, monitor soil quality that are helping to improve the overall harvest quality and accuracy.  

Artificial Intelligence (AI) in Agriculture Market Major Driving Forces

Growing Population: The rising global population, leading to increased demand for food. Growing population creating pressure on the agriculture industry to produce more food while using fewer resources. Artificial intelligence has potential to transform food systems by boosting yields, reducing costs, and developing more sustainable ecosystem in agriculture.

Consumer Preferences: The demand for artificial intelligence (AI) in agricultures is influenced by the shift in consumer preferences towards high-quality, safe, and traceable food.  Artificial intelligence enables precision agriculture and automation that enhances food quality and reducing environmental impact of traditional farming process.

Supportive Government Initiatives: Many governments across the globe are implementing several farmers welfare schemes to revitalize the agriculture industry. Governments have recognized the potential of AI in agriculture and are implementing supportive initiatives including funding programs, research grants, and investing in research and development for foster AI adoption.  

Rising Need for Real-time Data by Farmers: The growing need for real-time data largely and increasing agricultural activities drive the market for AI in agriculture. Real-time data from agricultural farms help make precision decision regarding preventive measures. Real-time data and analysis enable early detection, preventing water waste together with potential crop damage.

Artificial Intelligence (AI) in Agriculture Market Key Opportunities

Sustainable Farming Practices: Artificial intelligence algorithms enable autonomous crop management when integrate with IoT. AI systems minimizing water waste by adapting to real-time soil moisture levels and weather conditions. AI algorithms can decide in real-time how much water to provide to crops with the help of sensors. It can also help with the reducing pesticide and fertilizer use which minimizing environmental impact.

Usage of Drones in Agricultural Farms: The increasing usage of drones in agriculture to improve farming are expected to create opportunities for the market. Drones are able to capture very accurate soil health information including moisture levels so that water can be distributed in a field in the most efficient way in an effort to conserve resources. Integrating drone analytics and AI in agriculture presents tremendous potential for optimizing agricultural operations.

Integration of AI with IoT: The integration of AI with IoT devices in agricultural farms provides opportunities for enhanced connectivity and obtain accurate information. AI combined with IoT to monitor, measure, and store data in real-time. Moreover, AI with IoT helps to solve the common problem of labor shortages.

Artificial Intelligence (AI) in Agriculture Market Key Trends

·         Integrating drone analytics and AI in agricultural farms offers tremendous potential for optimizing agricultural operations 

·         Cloud-based AI solutions for making AI more accessible and affordable for small sized farms

·         Integration of machine learning and data analytics   is an emerging market trend to make real-time decisions

·         Technological advancements in robotic technologies for the development of autonomous tractors, weeding robots, and other robots automating farm operations

·         Implementing sustainable farming practices by adapting to real-time soil moisture levels and weather conditions with the help of AI

·         Increased use of AI-based robots for farm harvesting with more accuracy and speed, as robotic machines are more capable of doing bulk harvesting

Region-wise Market Insights

North America accounted for the largest market share at 33.2% in 2022 whereas, Asia Pacific is expected to register the fastest growth, expanding at a CAGR of 24.1% between 2023 and 2030.

In North America, the demand is driven by well-developed infrastructure, existence of some prominent players, and growing demand for advanced agricultural solutions in the region. Additionally, the North American market for AI in agriculture has been witnessing significant growth due to increasing adoption of AI technologies in the agriculture industry, rising demand for precision farming techniques, and need for increased productivity. In Europe, the market growth is attributed to the growing interest in the applications of artificial intelligence in the agriculture sector. Europe emphasizes on sustainable practices to reduce environmental impact driven by environmental concerns. In Asia-Pacific, the market is characterized by large agricultural sector, growing population, increasing demand for food safety, and adoption of advanced technologies in the region. Furthermore, the growth can be attributed to the government initiatives and support for the adoption of AI technology, and high adoption of AI in agricultural sector by major countries such as China, India, South Korea, and Japan. The Middle East and Africa has been witnessing a growing demand for AI in agriculture industry due to growing government initiatives to modernize agriculture and rising climate challenges in the region.

Market Competition Landscape

The global artificial intelligence (AI) in agriculture market is fragmented with the major companies with the involvement of various technology companies. Key players in the artificial intelligence (AI) in agriculture market have adopted various business strategies aimed at gaining a competitive edge. These strategies include product innovation, design differentiation, and the incorporation of sustainable and eco-friendly practices to meet evolving consumer preferences. Furthermore, these companies have adopted partnerships, mergers, acquisitions, and business expansion to expand their global reach and improve their technological products. Established brands leverage their reputation for quality and reliability to maintain market share, while newer entrants focus on disruptive innovations and unique selling propositions.

Key players in the global artificial intelligence (AI) in agriculture market implement various organic and inorganic strategies to strengthen and improve their market positioning. Prominent players in the market include:

·         Microsoft Corporation

·         IBM Corporation.

·         Granular Inc.

·         Deere & Company

·         aWhere Inc.

·         The Climate Corporation

·         Farmers Edge Inc.

·         Prospera Technologies Ltd.

·         Gamaya SA

·         Amazon Web Services

·         Oracle Corporation

·         Google LLC

·         Corteva, Inc.