Artificial Intelligence In Agriculture Market Size, Share and Trends 2026 to 2035

What is the Artificial Intelligence in Agriculture Market Size?

The global artificial intelligence in agriculture market is accounted at USD 2.57 billion in 2025 and predicted to increase from USD 3.17 billion in 2026 to approximately USD 20.12 billion by 2035, representing a CAGR of 22.85% from 2026 to 2035.

Artificial Intelligence In Agriculture Market Key Takeaways

• North America contributed more than 39% of the revenue share in 2025.
• By component, the software segment is expected to dominate the market during the forecast period.
• By technology, the predictive analytics segment captured more than 47% of revenue share in 2025.
• By application, precision farming is expected to capture the largest market share over the forecast period.

What is Artificial Intelligence in Agriculture?

Artificial Intelligence (AI) has emerged as a transformative force in the agriculture sector, revolutionizing the way farming and related activities are conducted. AI technologies, such as machine learning , computer vision, and data analytics , are being harnessed to overcome these challenges and unlock the full potential of agriculture. AI in agriculture goes beyond conventional farming practices, enabling farmers and agricultural stakeholders to leverage data-driven insights and intelligent decision-making to enhance productivity, optimize resource utilization, and address various agronomic issues.

This integration of AI in agriculture allows for the collection and analysis of vast amounts of data from diverse sources such as weather patterns, soil conditions, crop health and historical farming data. By processing and interpreting this data, AI systems can provide valuable information to farmers, enabling them to make well-informed decisions to improve yields, reduce waste, and minimize environmental impacts. One of the significant benefits of AI in agriculture is the automation of repetitive tasks through the use of smart machinery and robotics. These advancements help alleviate labor shortages and allow farmers to focus on higher-level strategic planning and management.

Artificial Intelligence In Agriculture Market Growth Factors

AI-powered agricultural technologies facilitate precision farming practices, where each crop or even individual plant can be treated uniquely based on their specific needs. This level of precision ensures efficient use of resources, reduces chemical inputs, and ultimately promotes sustainable agricultural practices. The artificial intelligence market is being driven by several factors including a growing population along with increasing demand for food, technological advancements, data-driven decision-making, advancements in robotics and drones, increasing government initiatives, growing investment in AgTech Startups, and increasing utilization of AI in crop monitoring.

Market Outlook

• Market Growth Overview: The artificial intelligence in agriculture market is expected to grow significantly between 2025 and 2034, driven by the increasing demand for food that requires higher productivity, enhanced efficiency, and yield, and rising precision agriculture.
• Sustainability Trends: Sustainability trends involve precision and regenerative agriculture, AI-driven automation and robotics, and predictive analytics and climate resilience.
• Major Investors: Major investors in the market include Deere & Company, Bayer AG, Microsoft Corporation, IBM Corporation, AGCO Corporation, and Corteva Agriscience.

Market Scope

Market Dynamics

Driver

Increasing population and food demand

The world population continues to grow, leading to a higher demand for food production. AI technologies in agriculture enable farmers to improve crop yields and optimize resource utilization to meet the increasing food demands sustainably. For instance, in mid-November 2022, there were 8.0 billion people on the planet. The global population is projected to rise by about 2 billion people over the next 30 years, from the present 8 billion to 9.7 billion in 2050. Such a rising population grows the demand for faster crop yield, AI is capable of reducing the pace of agricultural activities in multiple ways. Thus, the growth in the population and increasing food demand are expected to drive market growth over the forecast period.

Restraint

High-cost and unskilled labor

The high initial cost of installation is a significant barrier to this industry expansion. Low-income households in rural regions, among others, find the cost of smart agriculture to be an impassable obstacle depending on the specifications, which inhibits the general adoption of such advanced systems. Due to fragmented land and the high initial cost, there is no standardization of the enormous quantity of cumulative data, which results in an inefficient allocation of resources that significantly limits the market expansion over the analysis period.

Opportunity

Shortage of labor

The shortage or lack of skilled laborers for agricultural activities acts as a contributing factor for the adoption of artificial intelligence techniques. The lack of labor for such activities is caused by less interest by the younger population in the agricultural sector. Due to the same, private and public entities are rapidly investing in artificial intelligence-based automation systems to overcome the challenge of labor shortage. Multiple countries with aging populations are prone to adopt such technologies to address the shortage of workers on the field. Such challenges are expected to open a plethora of opportunities for the market's growth.

Component Insights

Based on the component, the global artificial intelligence in the agriculture market is segmented into hardware, software, and services. The software segment is expected to dominate the market over the projected period. One of the main drivers driving the expansion of software in AI in the agriculture market is the simplicity with which it can be integrated into agricultural machines, along with labor cost savings and real-time data collecting. The vast quantity of data being produced and saved in the cloud, together with the use of analytical tools, aids the farmer in identifying and managing every part of farming. The software greatly improves farmers' ability to make the necessary adjustments to the changing requirements.

For instance, the 'Farm Assist' application, which gathers data from sensors installed in farms via access points to a company's cloud and enables users to monitor and manage farm conditions using smartphones and PCs, was developed by NTTDOCOMO (a major telecommunications company in Japan) and released in April 2022 that it would use IAR's full development toolchain. During the projection period, such innovations will sharply boost this market's growth.

Technology Insights

Based on the technology, the global market is segmented into machine learning & deep learning, predictive analytics , and computer vision. Predictive analytics is expected to hold a significant market share over the forecast period. Predictive analytics is a subset of AI that involves the use of historical data, machine learning algorithms, and statistical techniques to make predictions about future events or outcomes. In the context of agriculture, predictive analytics is becoming increasingly important in helping farmers optimize their operations, make informed decisions, and mitigate risks. Predictive analytics models analyze historical data related to crop yields, weather conditions, soil health, and other relevant factors.

In addition, predictive analytics can be used to monitor and analyze data from various sources, such as weather patterns, crop health data, and pest populations. By detecting early warning signs of potential pest or disease outbreaks, farmers can take preventive measures to protect their crops and reduce the need for extensive pesticide use. Thus, these applications are expected to propel the market growth.

Application Insights

Based on the application, global artificial intelligence in the agriculture industry is segmented into precision farming, drone analytics, agriculture robots, livestock monitoring and others. Precision farming is expected to capture the largest market share over the forecast period. Some of the key drivers propelling the growth of this market are increased water efficiency, decreased fertilizer and pesticide use, and real-time data collecting of numerous crop characteristics.

By identifying the nutrient levels in soil, modern technologies like IoT, ML, sophisticated sensors, and big data analytics play a crucial role in boosting agricultural productivity and preventing the deterioration of soil health. This allows farmers to precisely apply the minerals needed in specific areas according to the data gathered. Global adoption of these contemporary agricultural practices is being sparked by several external causes, including a growing population, an increase in food demand, and climate change.

For instance, in March 2022, using a system of ML-equipped cameras with a sensitivity level according to the size of the weeds to be sprayed, John Deere announced the debut of a system for precisely spraying weeds exclusively on fallow areas. Thus, this kind of innovation is expected to drive the segment growth.

Regional Insights

U.S. Artificial Intelligence In Agriculture Market Size and Growth 2026 to 2035

The U.S. artificial intelligence in agriculture market size is accounted for USD 701.61 million in 2025 and is projected to be worth around USD 5,678.04 million by 2035, poised to grow at a CAGR of 23.26% from 2026 to 2035.

North America is expected to hold the largest share of the market while maintaining its dominance throughout the forecast period. Farmers and agricultural enterprises in North America are embracing AI technology to increase productivity, optimize resource allocation, and strengthen decision-making procedures. Precision agriculture, remote sensing, crop monitoring, predictive analytics, and automated farming systems are just a few of the agricultural uses of AI in the region. Farmers may enhance yields, save costs, lower risks, and make data-driven choices with the aid of this technology.

Additionally, governments in North America are putting supporting policies and programs in place in response to the promise of AI in agriculture. To encourage the use and innovation of AI in the agriculture industry, they include financing initiatives, research grants, and legislative frameworks. Such initiatives support the development of resilient and sustainable agriculture methods while creating a favorable environment for the expansion of the AI industry.

U.S. Artificial Intelligence in Agriculture Market Trends

The U.S.'s rising need for data analytics, machine learning, and computer vision optimizes planning, irrigation, and harvesting, rising use of water, fertilizers, and pesticides reduces environmental impact. Rising use in precision farming, crop monitoring, and health fuels the market growth.

For instance, in January 2023, through the application of artificial intelligence (AI), the United States and the European Union formed a partnership to enhance agriculture, climate forecasting, emergency response, and the electrical grid. The White House, which serves as the executive branch of the 27-member European Union, and the European Commission are now working together. Thus, this is expected to drive the market growth in the region.

The Asia Pacific is expected to grow at the highest CAGR over the forecast period. Population growth, climate change, and water shortage are the main reasons driving the AI Agriculture market in the region. Growing automation, technical developments like AI and ML, and declining soil quality will all fuel this market's expansion in this area. The "Global Action on Green Development of Special Agricultural Products: One Country One Priority Product (OCOP) in Asia and the Pacific" initiative, which the Food and Agriculture Organization of the United Nations (FAO) launched in May 2022, requires countries in the region to participate by creating green value chains and marketing their special agricultural products abroad. Such changes will fuel market expansion.

China Artificial Intelligence in Agriculture Market Trends

China's growth is driven by AI for automated planning, spraying, harvesting, and monitoring, tackling labor shortages, and rising demand for cloud-based platforms for real-time analytics. Rising digital systems use sensors, satellite data, and AI to optimize water use in arid places.

How Did Europe Experience Notable Growth in the Artificial Intelligence in Agriculture Market?

Europe is rapidly adopting AI-driven precision farming and robotics to guarantee regional food security and operational efficiency, thereby transforming Europe into a global leader in sustainable, data-centric agricultural technology.

Germany Artificial Intelligence in Agriculture Market Trends

Germany's rising use of robotic solutions for tasks, such as weeding, milking, and barn cleaning, the need to reduce costs, water, and improve yields, and the rising applications in crop management, livestock monitoring, and yield optimization. Adoption of AI-driven technologies such as machine learning, computer vision, and sensor data analytics is enabling more informed decision-making and optimized resource use across crop production and livestock management.

Top Artificial Intelligence in Agriculture Market Companies and their Offerings:

• Microsoft: Offers the Azure FarmBeats platform, which is a combination of machine learning, IoT sensors, drones, and satellite data, which is used in precision farming.
• IBM Corporation: Provides Watson Decision Platform in Agriculture with predictive cases of bad weather, crop health, and soil information using AI technology.
• Granular, Inc.: Emerges Granular Insights farm management application that uses local data analysis to enhance operational planning and field-level profitability mapping.
• AgEagle Aerial Systems Inc.: Offers a drone-based data service in the agricultural sector based on computer vision and AI to monitor crop health at a high resolution.

Artificial Intelligence in Agriculture Market Companies

• Microsoft
• IBM Corporation
• Granular, Inc.
• AgEagle Aerial Systems Inc.
• The Climate Corporation
• Deere & Company
• Descartes Labs, Inc.
• Prospera Technologies
• GAMAYA
• aWhere Inc.
• Taranis
• ec2ce
• VineView
• PrecisionHawk
• Tule Technologies Inc.

Artificial Intelligence in Agriculture Market Companies

• Microsoft: Microsoft contributes to AI in agriculture by providing cloud computing infrastructure and services, like Azure AI, which enable the development and deployment of AI-driven agricultural solutions for tasks such as predictive analytics and farm management.
• IBM Corporation: IBM leverages its Watson AI platform and cloud services to offer cognitive agriculture solutions that help farmers with real-time data analysis, weather forecasting, and crop yield prediction.
• Granular, Inc.: Now part of Corteva Agriscience, Granular provides digital tools and farm management software that use AI to help farmers with operational decisions, profitability analysis, and land management.
• AgEagle Aerial Systems Inc.: AgEagle focuses on data acquisition through unmanned aerial systems (drones) and uses AI for processing the collected aerial imagery to provide actionable insights for precision farming.
• The Climate Corporation: A subsidiary of Bayer, The Climate Corporation utilizes its FieldView platform to integrate vast amounts of field data and apply AI models to provide farmers with customized recommendations for planting, fertilizing, and harvesting.
• Deere & Company: John Deere incorporates AI and machine learning into its heavy machinery and the John Deere Operations Center to automate tasks, enable precision planting and harvesting, and provide real-time field data analysis.

Segments Covered in the Report

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