AI in Agriculture Market

AI in Agriculture Market Size and Share:

The global AI in agriculture market size was valued at USD 2.18 Billion in 2024. Looking forward, IMARC Group estimates the market to reach USD 12.95 Billion by 2033, exhibiting a CAGR of 19.48% during 2025-2033. North America currently dominates the market, holding a significant market share of over 36.8% in 2024, driven by the increasing need for precision agriculture techniques to enhance crop yield, and the growing adoption of IoT devices and sensors for data-driven farming practices.

The global AI in agriculture market is driven by the growing need for precision farming to significantly upgrade resource consumption and improve crop productivity. Elevating concerns about climate change and sustainable agricultural methods, combined with escalating food requirement worldwide, further bolsters the deployment of AI in this industry. Besides this, rapid innovations in IoT technologies, machine learning (ML), and robotics facilitate automated decision-making, real-time monitoring, and predictive analysis, substantially advancing operational efficacy. In addition, notable increase in government subsidies and ventures actively incentivize smart farming solutions, coupled with the amplifying utilization of AI-based equipment and drones, contributing to creating a positive AI in agriculture market outlook.

The United States exhibits an integral role in the global AI in agriculture industry, driven by advanced technological infrastructure and widespread adoption of precision farming practices. For instance, industry reports indicated that as of 2024, more than 70% of farmers in the United States currently implement at least one precision agriculture technique. In certain scenarios, these advanced farming practices have demonstrated the potential to boost crop yields by as much as 30%. Furthermore, with notable elevation in investments for research and development initiatives, the country incentivizes advancements in AI-based services, encompassing automated irrigation systems, crop monitoring, and yield forecast. Moreover, the U.S. extensively profits from a resilient agribusiness segment, aided by government programs endorsing resource efficacy and sustainable farming. In addition, the strong presence of major market players and tactical partnerships amongst agricultural firms and technology providers further fortify the United States' position as a leading nation in AI-powered agricultural innovations.

AI in Agriculture Market Trends:

Increased efficiency and productivity

One of the primary factors driving the adoption of AI in the agriculture market is the significant increase in efficiency and productivity it offers. It has been reported that, AI in farming increases crop yields by up to 30%. Traditional farming methods often involve a lot of guesswork and manual labor, which can be both time-consuming and prone to errors. AI technologies, such as machine learning algorithms and data analytics, enable farmers to make more informed decisions about planting, watering, and harvesting. For example, AI-powered systems can analyze soil conditions, weather patterns, and crop health, optimizing irrigation schedules and reducing water waste. This precision farming approach leads to higher crop yields and better resource management, making agriculture more sustainable and profitable in the long term.

Labor shortage and cost reduction

Labor shortages in agriculture are a global issue, with many regions facing difficulties in securing a stable and skilled workforce for farming activities. According to reports, the global labor shortage in 2023 was 77% an increase of 2% from previous year. AI and automation offer a solution to this challenge by reducing the reliance on manual labor. Robotics, for instance, can perform tasks like weeding, harvesting, and even fruit picking, which are labor-intensive and often hard to staff. Additionally, AI systems can monitor and manage large areas of farmland, reducing the need for a large on-site workforce. This automation not only addresses the labor shortage but also contributes to cost reduction. By automating routine tasks, farmers can lower their operational costs and focus their resources on more strategic aspects of farm management, thus fostering a stable AI in agriculture market growth.

Technological advancements

The rapid advancements in AI and machine learning technologies are key drivers in the AI in Agriculture market. As per the IMARC Group, the global machine learning market reached USD 31.0 Billion in 2024. These technologies have evolved significantly, offering sophisticated solutions for complex agricultural challenges. Machine learning algorithms can process vast amounts of data from various sources, including weather patterns, crop health, and soil conditions, to provide precise and real-time insights for farmers. The integration of AI in agricultural machinery, like autonomous tractors and drones, enhances field operations, reducing labor costs and increasing efficiency. This continuous evolution of AI technologies makes them increasingly accessible and applicable in agriculture, thereby increasing the AI in agriculture market demand.

Need for sustainable agriculture practices

Sustainability is a major concern in modern agriculture, and AI plays a crucial role in promoting sustainable practices. AI-driven tools help in monitoring and reducing the environmental impact of farming by optimizing the use of resources. The 2023 Farm Practices Survey (FPS) indicated that 62% of farmers thought it important to consider GHGs when making farm business decisions. For instance, AI systems can provide precise data on the amount of water or pesticides needed for specific crop areas, minimizing wastage and environmental harm. Additionally, AI can assist in crop rotation and soil health management, which are essential for long-term sustainability. By reducing the carbon footprint and promoting eco-friendly practices, AI is not just an agricultural tool but also a means to combat climate change.

AI in Agriculture Industry Segmentation:

IMARC Group provides an analysis of the key trends in each segment of the global AI in agriculture market, along with forecast at the global, regional, and country levels from 2025-2033. The market has been categorized based on offering, technology, and application.

Analysis by Offering:

• Software
• Hardware
• AI-as-a-Service
• Services
   

Software stands as the largest offering in 2024, holding around 55.9% of the market. The software segment represents the dominant segment in the AI in Agriculture market industry, mainly propelled by the accelerating shift of agricultural firms as well as farmers toward of AI-powered decision support systems, AI-driven farm management software, and data analytics platforms. Such software services provide critical attributes, mainly including irrigation management, crop monitoring, yield prediction, and effective detection of pest, facilitating data-based and accurate agricultural practices. In addition, with the growing deployment of AI algorithms, farmers can significantly improve crop yields while lowering the harmful impact on ecosystem, easily form insight-based decisions, and upgrade resource consumption. Moreover, this segment is anticipated to experience substantial expansion as technological firms continue to design leading-edge software services customized to the transforming demands of the agriculture industry.

Analysis by Technology:

• Machine Learning
• Computer Vision
• Predictive Analytics
   

Machine learning leads the market with around 53.3% of market share in 2024. Machine learning stands out as the largest segment. Machine learning algorithms are widely used for data analysis, pattern recognition, and decision-making in agriculture. They enable farmers to harness the power of data from various sources, including sensors, satellites, and drones, to make informed decisions about planting, irrigation, pest control, and crop health. In addition to this, machine learning models help optimize resource allocation, predict crop yields, and even identify early signs of diseases or nutrient deficiencies in crops. Furthermore, the scalability and versatility of machine learning make it a fundamental technology driving precision agriculture and sustainable farming practices.

Analysis by Application:

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

Precision farming leads the market with around 40.0% of market share in 2024. Precision farming, also widely termed as precision agriculture, dominates this market segment with its robust emphasis on upgrading the practices pertaining to the crop management. Furthermore, this segment mainly envelops the heavy deployment of AI-powered technologies for accurate monitoring of plant health, soil conditions, as well as weather status. Besides this, it facilitates farmers to make data-based decisions associated with pest control, irrigation, and fertilization, as a result leading to amplified resource effectiveness and crop yield. In addition to this, precision farming also facilitates the trend of sustainability by significantly lowering adverse impact on environment and resource wastage, thereby positioning it as a crucial and most impactful segment in expanding the AI in Agriculture market share.

Regional Analysis:

• North America
  • United States
  • Canada
• Asia-Pacific
  • China
  • Japan
  • India
  • South Korea
  • Australia
  • Indonesia
  • Others
• Europe
  • Germany
  • France
  • United Kingdom
  • Italy
  • Spain
  • Russia
  • Others
• Latin America
  • Brazil
  • Mexico
  • Others
• Middle East and Africa
   

In 2024, North America accounted for the largest market share of over 36.8%. North America dominates the market, driven by cutting-edge technological infrastructure and a strong focus on precision farming. Furthermore, heavy investments in AI adoption also fosters AI in agriculture market growth across this region. For instance, in May 2024, -Carbon Robotics, a U.S.-based AI-powered agriculture company, announced receival of significant investment from NVentures to advance agriculture by leveraging AI. Besides this, North America heavily benefits from the presence of leading AI solution providers, and the agriculture sector's willingness to embrace innovative technologies like AI for crop monitoring, soil analysis, and autonomous machinery. Favorable government policies and incentives also contribute to the market's growth in North America.

Key Regional Takeaways:
 

United States AI in Agriculture Market Analysis

In 2024, United States accounted for 89.00% of the market share in North America. The increasing need for food driven by population growth is creating promising opportunities in the market. As per the United States Census Bureau, the US population estimated at 334,233,854 on January 1, 2023. As the U.S. population grows, so does the demand for food items. However, arable land and water resources are limited, making it essential to maximize agricultural productivity. AI-powered tools like precision farming systems, which use data analytics and predictive modeling, help farmers optimize resource use, enhance crop yields, and reduce waste. In line with this, the integration of Internet of Things (IoT) devices with AI is transforming U.S. agriculture. Field sensors gather real-time information on soil moisture, weather conditions, and crop health, which is processed by AI algorithms to deliver practical insights and recommendations. Companies are focusing on developing autonomous tractors and AI-driven equipment, which streamline planting, harvesting, and monitoring processes, thereby reducing labor costs and increasing efficiency. Furthermore, U.S. government programs and funding are encouraging the adoption of AI in agriculture. For instance, the USDA’s Agriculture Innovation Agenda promotes technologies that increased productivity while reducing environmental impact. Federal funding for AI research in agriculture is also surging, which is driving innovation in areas like pest detection and yield prediction. Besides this, AI plays a critical role in addressing the challenges posed by climate change. Predictive models help farmers adapt to changing weather patterns by identifying optimal planting times and crop varieties. Sustainable farming practices, enabled by AI, align with growing consumer and regulatory demands for eco-friendly agriculture.

Asia Pacific AI in Agriculture Market Analysis

The Asia Pacific region is witnessing rapid growth in the adoption of artificial intelligence (AI) in agriculture, driven by factors, such as increasing food demand, technological advancements, climate resilience needs, and supportive government initiatives. The region is home to more than half of the world's population, with countries like India and China experiencing significant population growth. This is leading to higher demand for food production in a region already facing limited arable land and water resources. According to the First Advance Estimates by IBEF for the year 2023 to 2024 (Kharif only), total production of foodgrain in the nation is estimated at 148.5 million tons. AI-driven solutions like precision agriculture and smart irrigation systems optimize resource use, boost yields, and reduce waste. Apart from this, the region has seen a surge in agri-tech start-ups as they are developing AI solutions for agriculture. These advancements, ranging from drone-enabled crop surveillance to AI-driven soil evaluation, are revolutionizing conventional agricultural methods. Japan, for example, is leveraging AI for robotic harvesting and pest detection, addressing labor shortages in agriculture. Additionally, the availability of affordable IoT devices and cloud-based platforms is making AI adoption more accessible for small and medium-sized farmers. Furthermore, the Asia Pacific region is highly vulnerable to climate change, with unpredictable weather patterns affecting agriculture. AI tools enable farmers to analyze historical and real time data for better decision-making, improving resilience to droughts, floods, and other climate-related challenges. AI-enabled pest and disease management tools are also gaining traction in the region, helping reduce crop losses. 

Europe AI in Agriculture Market Analysis

The adoption of artificial intelligence (AI) in agriculture across Europe is gaining momentum due to the demand for sustainable farming, labor shortages, technological innovations, and supportive regulatory frameworks. Europe is at the forefront of adopting sustainable agricultural practices, driven by the European Green Deal and Farm to Fork Strategy, which aim to reduce environmental impact and promote resource efficiency. AI-powered tools, such as precision agriculture systems and smart irrigation reduce water usage, optimize fertilizer application, and minimize waste. Additionally, there is a rise in the demand for food products on account of the population growth. As of January 2023, around 448.8 Million individuals dwelled in the European Union (EU). The most populous EU country was Germany with 84.4 Million, 19% of the EU total, as reported by the Eurostat. Apart from this, labor shortages in the agricultural sector are a significant challenge in Europe, particularly in countries like Germany, France, and the UK. AI-powered robotics and autonomous machinery are addressing this issue by automating labor-intensive tasks such as planting, weeding, and harvesting. Major companies in the region are developing AI-driven robots for weed management, reducing dependency on manual labor and chemical herbicides. Moreover, Europe has a thriving ecosystem of agri-tech start-ups and research institutions, which is driving innovation in AI applications. Technologies like drone-based crop monitoring, AI-driven soil analysis, and yield prediction are gaining popularity. For instance, Dutch start-ups are leveraging AI to optimize greenhouse farming, significantly enhancing productivity in controlled environments.

Latin America AI in Agriculture Market Analysis

The adoption of artificial intelligence (AI) in agriculture is accelerating in Latin America, driven by the need to enhance productivity, adapt to climate change, and address resource challenges. With a rising population and a critical role as a global food exporter, Latin America is turning to AI to boost agricultural efficiency. According to reports, Brazilian agribusiness exports hit a record in 2023, reaching USD 166.55 Billion. Technologies like AI-powered crop monitoring and precision farming optimize resource use, helping increase yields and reduce waste. The region faces significant climate challenges, such as droughts and unpredictable weather. AI-powered tools process weather data to deliver practical insights, enabling farmers to make well-informed choices regarding planting and harvesting activities. Moreover, countries like Brazil and Argentina are investing in AI-driven solutions, including drones, sensors, and robotics, to modernize farming practices. Furthermore, public policies and private sector investments are fostering innovation, making AI technologies more accessible to farmers.

Middle East and Africa AI in Agriculture Market Analysis

The Middle East and Africa (MEA) region is experiencing a growing adoption of artificial intelligence (AI) in agriculture, driven by the need for food security, resource optimization, and technological advancements. Rapid population growth and increasing food demand is highlighting the need for efficient farming practices. AI tools like precision agriculture and crop monitoring systems help improve yields and reduce food wastage, crucial in regions with limited arable land. AI-driven irrigation systems are addressing water scarcity, a critical issue in the arid Middle East. As per the report ‘Economics of Water Scarcity in MENA: Institutional Solutions’ by the end of this decade, the amount of water available per capita annually will fall below the absolute water scarcity threshold of 500 cubic meters per person, per year. Smart irrigation technologies, using AI to monitor soil and weather conditions, benefit in reducing water usage. Furthermore, supportive policies and private investments are facilitating the integration of AI technologies, driving market growth in the region.

Competitive Landscape:

The competitive landscape is exhibited by the robust establishment of advanced startups as well as key technology companies that actively provide innovative AI-powered services. Major industry players are currently emphasizing on yield prediction, precision farming, resource optimization, and plants monitoring. In addition to this, various firms are actively opting for machine learning (ML) algorithms, AI-driven drones, and robotics, to improve both sustainability and productivity. Furthermore, tactical acquisition, mergers, and partnerships are extensively prevalent as companies strive to proliferate their geographical foothold as well as portfolios. For instance, in October 2024, Google announced strategic partnership with Indian-based local startups to boost implementation of AI in key sectors of the nation, including agriculture and sustainability. Besides this, elevating investments in research and development initiatives and the implementation of AI in agribusiness by both agritech firms and large-scale farms further boost competition.

The report provides a comprehensive analysis of the competitive landscape in the AI in agriculture market with detailed profiles of all major companies, including:

• A.A.A Taranis Visual Ltd.
• Ag Leader Technology
• AgEagle Aerial Systems Inc.
• Bayer AG
• Deere & Company
• Gamaya
• Granular Inc. (DuPont de Nemours, Inc.)
• International Business Machines Corporation
• Raven Industries Inc.
• Trimble Inc.
• Oracle Corporation
• Wipro Limited
   

Latest News and Developments:

• August 2024: The Ministry of Agriculture, India launched the National Pest Surveillance System (NPSS), which employs AI and ML for pest management. This initiative aims to reduce crop losses and enhance productivity through real-time data and automated advisories.
• July 2024: Google announced the launch of the Agricultural Landscape Understanding (ALU) tool in India, designed to enhance farming practices through AI and data-driven insights. This tool will utilize high-resolution satellite imagery and machine learning to provide detailed information on crop types, field sizes, irrigation, and market access. Collaborating with various organizations, including the Indian government, it aims to address challenges faced by farmers.
• May 2024: The Uttar Pradesh government aims to enhance the rural economy by promoting agricultural startups and integrating AI in farming. Plans include hosting the "Krishi Bharat" global farmers’ summit in November 2024, attracting delegations from various countries. The initiative will also involve sending progressive farmers abroad for knowledge exchange and showcasing agri-tourism through local farm visits.
• January 2023: The U.S. Department of State and the EU's DG CONNECT signed an "Administrative Arrangement on Artificial Intelligence for the Public Good." This agreement aims to enhance cooperation in AI research to tackle global challenges like climate change and natural disasters. It emphasizes joint efforts between U.S. and EU researchers to develop AI applications that improve disaster response, agriculture, and healthcare. The initiative also seeks to share resources with international partners lacking capabilities to address these challenges effectively.

AI in Agriculture Market Report Scope:

Key Benefits for Stakeholders:

• IMARC’s report offers a comprehensive quantitative analysis of various market segments, historical and current market trends, market forecasts, and dynamics of the AI in agriculture market from 2019-2033.
• The research study provides the latest information on the market drivers, challenges, and opportunities in the global AI in agriculture market.
• The study maps the leading, as well as the fastest-growing, regional markets. It further enables stakeholders to identify the key country-level markets within each region.
• Porter's Five Forces analysis assists stakeholders in assessing the impact of new entrants, competitive rivalry, supplier power, buyer power, and the threat of substitution. It helps stakeholders to analyze the level of competition within the AI in agriculture industry and its attractiveness.
• Competitive landscape allows stakeholders to understand their competitive environment and provides an insight into the current positions of key players in the market.