AI in Agriculture Market 2024 – Market Size & Segments Analysis, Industry Trends, Manufacturers Analysis, Opportunities and Forecast 2030

The global market value of AI in the agriculture market was valued at USD 1.5 billion in 2022, and a CAGR of 7.5% is expected during the forecast period. Increasing demand for precision agriculture and making farmers more efficient and productive is driving growth in the market significantly. AI is used in many areas of farming, like field farming, crop health, irrigation systems, and livestock. Machine learning, predictive analysis, and computer visions are driving growth in the market significantly.

AI in the agriculture market has been expanding significantly, with projections suggesting robust growth in the coming years. Growth is driven by the need for sustainable farming practices, increasing food demand to population growth, and the rising adoption of precision farming technologies. AI is used to analyze data from sensors and satellite imagery to make precise decisions about planting, watering, and fertilizing, which helps optimize resource use and improve crop yields.

Growth Drivers

Drones and robots powered by AI are increasingly used for tasks such as planting, surveying, and harvesting, reducing the need for manual labor and improving efficiency. AI helps in optimizing the supply chain by predicting demand, managing logistics, and reducing waste. AI is used to analyze data from sensors and satellite imagery to make precise decisions about planting, harvesting, and fertilizing, which helps in optimizing resource use and improving crop yield. AI tools analyze satellite images, drone footage, and sensor data to monitor crop health, detect diseases, and predict yield outcomes.

Increasing demand by agriculture to help farmers optimize their farmers inputs like water, fertilizers, and pesticides based on real-time data, reducing waste, and improving crop quality. Autonomous robots and drones powered by AI perform tasks such as planting, harvesting, and weed control in an efficient manner. AI models predict weather patterns and analyze soil conditions to advise on planting schedules, irrigation needs, and other critical decisions. Increased efficiency of agricultural supply chain by AI is the need of the hour.

With a growing population, there is a rising demand for food and increasing pressure on agriculture to produce more food sustainably. The agriculture sector faces a labor shortage, making automation and AI solutions more attractive. Progress in AI, machine learning, and the Internet of Things is driving innovation in agriculture.

Segmentation

Component

·         Hardware

·         Software

·         Services

Application

·         Precision Farming

·         Drone Analytics

·         Agriculture Robots

·         Livestock Monitoring

·         Labor Management

Deployment

·         Cloud

·         On-Premise

·         Hybrid

Regional Outlook

·         Asia Pacific

·         North America

·         Latin America

·         Europe

·         Middle East and Africa

AI in agriculture application Segmentation

On the basis of the application, the AI in agriculture is segmented into precision farming, drone analysis, agriculture robots, livestock monitoring, and labor management. Precision farming is generally the leading segment in the market and is expected to dominate the market during the forecast period. It generally involves the use of advanced technologies like GPS, IOT, and sensors to optimize field-level management concerning crop farming.

AI in precision farming allows farmers to optimize the use of inputs like water, fertilizers, and pesticides by analyzing soil, weather, and crop data. AI models predict crop yield based on historical data and current conditions, helping farmers increase productivity. Precision farming uses AI to analyze real-time data from various sources like satellite imagery, drones, and IoT devices. It enables continuous monitoring of crop health and early detection of issues such as pest life stations or diseases. Precision farming automates many tasks traditionally done manually.

AI in agriculture component Segmentation

On the basis of the component, the AI in agriculture component market is segmented into hardware, software, and services. Software is the leading segment in the market and is expected to dominate the market during the forecast period. The core of AI in agriculture lies in software that processes and analyzes data to provide actionable insights. This includes machine logarithms, predictive analytics, and decision support systems that help farmers optimize their operations. Software platforms that integrate various aspects of farm management, from crop monitoring to financial planning, are in high demand. Scalability, flexibility, and rapid innovation and adoption, along with lower initial investment, are driving growth in the market.

Regional Outlook

On the basis of the regions, the AI in agriculture market is segmented into 5 parts: Asia Pacific, North America, Latin America, the Middle East and Africa, and Europe. North America is the leading segment, and Asia Pacific is expected to dominate the market during the forecast period because of the well-established technological infrastructure that supports the development and deployment of AI solutions. The region is home to many leading tech companies, research institutions, and universities that drive innovation in AI technologies for agriculture. This strong research and development environment foster continuous advancements in AI applications.

North America has a high prevalence of large-scale commercial farming operations that have the financial resources and capacity to invest in AI technologies. The agricultural sector in North America is suffering from a labor shortage, especially in manual seasonal work. AI and automation offer solutions to this labor challenge issue, such as harvesters and drones. Growing emphasis on sustainable farming practices in North America, driven by both consumer demand and regulatory pressures, is driving growth in the market. Significant government support for innovation in agriculture includes funding and policies that encourage the adoption of AI and other advanced technologies.

The Asia-Pacific region, particularly countries like China and India, has a vast agricultural sector that supports a large portion of the global population. The need to increase productivity and efficiency in these densely populated countries drives adoption of AI technologies. Governments in countries like China and India are promoting the use of advanced technologies in agriculture to address food security issues and modernize farming practices. The region is witnessing a rise in investment from both government bodies and private sectors in agri-tech startups. These startups are developing AI-based solutions to fulfill the needs of local farmers. Rapid adoption of smart phones in local areas and use of the internet has brought a revolutionary change in the market. The region’s diverse climate and environmental challenges require tailored AI solutions to address specific agricultural needs.

 Key Players

·         IBM

·         Microsoft

·         Prospera

·         John-Deere

·         Microsoft

·         Taranis

·         The Climate Corporation

·         Ageagle Aerial Systems Inc.

·         Descartes Labs, Inc.

·         Other Players