# North America Applied Ai In Agriculture Market > North America Applied AI in Agriculture Market Research Report By Technology (Machine Learning, Computer Vision, Predictive Analytics), By Offering (Software, AI-as-a-Service), By Application (Drone Analytics, Precision Farming), and By Regional (US, Canada)-Forecast to 2035 - **Forecast Period:** 2025 - 2035 - **CAGR:** 29.32% - **2024:** $ 771.31 Million - **2025:** $ 997.45 Million - **2035:** $ 13,048.4 Million - **Key Players:** Bayer (DE), Corteva Agriscience (US), Syngenta (CH), John Deere (US), AG Leader Technology (US), Trimble (US), Taranis (IL), Farmers Edge (CA), Aker Solutions (NO) **Report ID:** MRFR/ICT/60448-HCR · **Pages:** 200 · **Author:** Nirmit Biswas & Aarti Dhapte · **Last Updated:** February 06, 2026 **URL:** https://www.marketresearchfuture.com/reports/north-america-applied-ai-in-agriculture-market-62284 --- ## Market Summary ## **North America Applied****AI****in Agriculture Market Overview** As per MRFR analysis, the North America Applied AI in Agriculture Market Size was estimated at 582 (USD Million) in 2023.The North America Applied AI in Agriculture Market is expected to grow from 753(USD Million) in 2024 to 13,047 (USD Million) by 2035. The North America Applied AI in Agriculture Market CAGR (growth rate) is expected to be around 29.602% during the forecast period (2025 - 2035). **Key North America Applied****AI****in Agriculture Market Trends Highlighted** Technological developments and an increasing emphasis on sustainability are driving notable trends in the North American Applied AI in Agriculture Market. One of the main factors propelling the market is the growing use of precision agriculture as farmers want to increase crop yields and improve resource management. Farmers may make better decisions by using integrated AI solutions, such as machine learning algorithms and data analytics, to understand more about weather patterns, pest control, and soil health. The need for automated technologies like drones and self-driving tractors is growing dramatically as agricultural practices change, indicating a move toward more productive farming methods. The North American market offers a wealth of options for investigation, particularly in the area of improving functional automation for labor-intensive operations. Innovation is being fostered by the region's agricultural organizations and institutions' continuous research and development projects. Another exciting possibility is partnerships between tech firms and agriculture stakeholders, which are aimed at developing intelligent technologies that will further simplify farming operations. Farmers are increasingly using AI-powered software for real-time analysis and forecasting as the trend toward data-driven farming has accelerated in recent years. This change is facilitated by the incorporation of Internet of Things (IoT) devices into AI platforms, which allow for continuous field monitoring and adaptation. Furthermore, since government programs encourage smart farming methods, which raise agricultural productivity and economic viability, North America's regulatory environment is starting to encourage the implementation of AI. These patterns mark a turning point in North American agriculture as the need for food keeps growing, opening the door to a more productive and sustainable future. Source: Primary Research, Secondary Research, _Market Research Future_ Database and Analyst Review **North America Applied****AI****in Agriculture Market Drivers** **Increasing Demand for Sustainable Farming Practices** In North America, the pressure to adopt sustainable agricultural practices is intensifying. The United States Department of Agriculture (USDA) reported that farms implementing sustainable practices can increase yields by up to 30 percent, while simultaneously reducing environmental impacts. This trend is driving the North America Applied AI in Agriculture Market as farmers seek innovative technologies to optimize resource management and enhance crop resilience. Companies like Deere & Company are developing advanced AI-driven solutions that help farmers monitor soil health and manage water usage more effectively, contributing to improved sustainability metrics in agriculture. With the need for sustainability top of mind, the integration of AI technologies aligns perfectly with the goals of reducing carbon footprints and increasing agricultural productivity, thereby propelling market growth in this region significantly. **Technological Advancements in Precision Agriculture** The North America Applied AI in Agriculture Market is witnessing robust growth due to rapid advancements in precision agriculture technologies. According to the American Farm Bureau Federation, the adoption of precision agriculture can lead to yield improvements of about 20 percent. Companies like Monsanto (Bayer) are pioneering the use of AI and machine learning to analyze complex data sets collected from farms, leading to more informed decision-making. Such technologies help farmers apply water, fertilizers, and pesticides more precisely, minimizing waste and reducing costs, which makes this a key driver for the market. As technology continues to evolve, farmers in North America are more inclined to leverage these advancements, further boosting the market potential. **Rising Labor Costs and Labor Shortages** Labor costs in agriculture are escalating in North America, increasing pressure on farmers to innovate. Recent reports from the National Agricultural Statistics Service highlighted a 10 percent increase in labor costs over the past five years. This trend has created a strong incentive for farmers to invest in automation and AI solutions that can mitigate their reliance on labor. For instance, companies like PrecisionHawk are developing AI-driven drones and robots designed for various agricultural tasks, which not only reduce labor costs but also enhance operational efficiency. This transformation is driving the North America Applied AI in Agriculture Market as more producers look to adopt AI technologies that can effectively fill the labor gap and streamline farm operations. **North America Applied****AI****in Agriculture Market Segment Insights** **Applied****AI****in Agriculture Market Technology Insights** In the North America Applied AI in Agriculture Market, the Technology segment plays a pivotal role in transforming agricultural practices through advanced solutions that enhance efficiency and productivity. Among the various technologies, Machine Learning has emerged as a significant component, enabling farmers to analyze vast amounts of data, leading to improved decision-making and resource optimization. It empowers predictive maintenance and helps in disease detection, thereby significantly driving yield. Computer Vision is another critical technology that allows for real-time monitoring and analysis of crops and livestock, thereby aiding in the automation of processes such as harvesting and quality assessment. This technology utilizes high-resolution imaging and deep learning algorithms, effectively identifying patterns that may be missed by the human eye, which is essential in maintaining food quality standards. Meanwhile, Predictive Analytics serves as a cornerstone in agricultural planning and management, utilizing historical data and real-time inputs to forecast future trends. This capability allows farmers to anticipate crop performance and market conditions, thus optimizing planting schedules and resource allocation. Collectively, these technologies represent the forefront of innovation in agriculture, significantly contributing to the sustainability and efficiency of farming practices across North America. With the ongoing advancements in artificial intelligence, the scope for these technologies is vast, thereby creating opportunities for increased investment and development in the sector. The emphasis on precision agriculture, driven by these technologies, is expected to continue reshaping the industry, presenting numerous economic benefits and enhancing food security across the region. The ability to leverage data and provide actionable insights is becoming increasingly essential for modern farmers aiming to meet the challenges posed by climate change and population growth, underscoring the importance of the Technology segment within the North America Applied AI in Agriculture Market. Source: Primary Research, Secondary Research, _Market Research Future_ Database and Analyst Review **Applied****AI****in Agriculture Market Offering Insights** The Offering segment of the North America Applied AI in Agriculture Market is significant, reflecting the increasing integration of advanced technologies in the agriculture sector. As agriculture evolves, there is a growing demand for Software and AI-as-a-Service solutions that facilitate precision farming, optimize resource use, and improve crop yield. Software solutions enable farmers to leverage data analytics for better decision-making, enhancing productivity through tailored recommendations. AI-as-a-Service, on the other hand, provides scalable and flexible AI tools that small to mid-sized farms can access without heavy upfront investments, thereby democratizing technology in agriculture. The growth in these offerings is further fueled by government initiatives aimed at modernizing agricultural practices and promoting sustainable farming methods across North America. The adoption of these technologies is therefore set to revolutionize traditional farming, making the Offering segment crucial for future market growth and innovation in agricultural practices. As the agriculture sector seeks to tackle challenges such as climate change, labor shortages, and food security, the importance of sophisticated tools and services will only continue to increase. **Applied****AI****in Agriculture Market Application Insights** The North America Applied AI in Agriculture Market is witnessing significant advancements with a focus on the Application segment, which includes essential areas such as Drone Analytics and Precision Farming. Drone Analytics has become increasingly vital as it provides farmers with real-time data to assess crop health, monitor livestock, and optimize field management, thus enhancing operational efficiency. Precision Farming leverages AI technology to analyze data related to soil health, weather patterns, and crop yield, enabling tailored farming strategies that substantially improve productivity and resource utilization. Both of these areas are gaining traction in North America, driven by growing demand for sustainable agriculture practices and the need for increased food production to meet the demands of a growing population. Furthermore, the integration of AI in these applications is empowering farmers to make informed decisions, reduce waste, and improve profitability. As innovations continue to emerge, the focus on these key areas within the North America Applied AI in Agriculture Market is expected to expand, offering significant opportunities for growth and transformation in the industry. **Applied****AI****in Agriculture Market Regional Insights** The North America Applied AI in Agriculture Market showcases significant growth potential driven by advancements in technology and increasing adoption of AI solutions among farmers and agricultural enterprises. The region splits primarily into the United States and Canada, with the United States holding a dominating share due to its extensive agricultural base and innovation ecosystem. This market segment is characterized by a strong urge for automation, enhancing crop yields, and optimizing resource utilization, offering considerable opportunities for major stakeholders in the industry. In Canada, the focus is on sustainable farming practices, where Applied AI technologies play a crucial role in precision agriculture. The integration of AI in agriculture is expected to accelerate farm productivity and better decision-making processes for farmers, addressing challenges such as labor shortages and climate change impacts. Both countries are witnessing an uptick in government initiatives and support for technology adoption in agriculture, which further propels the North America Applied AI in Agriculture Market forward. Market participants are also leveraging big data analytics and IoT to drive insights and efficiencies in farming operations, contributing to the overall growth dynamics within the region. Source: Primary Research, Secondary Research, _Market Research Future_ Database and Analyst Review **North America Applied****AI****in Agriculture Market Key Players and Competitive Insights** The North America Applied AI in Agriculture Market has been witnessing significant advancements and competitive dynamics in recent years, driven by increasing adoption of artificial intelligence technologies to enhance agricultural processes. The market is characterized by various players who are leveraging AI to optimize farming practices, improve crop yields, manage resources effectively, and ultimately drive higher profitability for farmers. The integration of AI-driven solutions into agriculture has opened up opportunities for innovative applications, ranging from precision farming and pest management to predictive analytics and crop monitoring. Competitors in this market are striving to differentiate their offerings and gain market share by focusing on research and development, forging partnerships, and addressing the growing demands for sustainable agricultural practices. Harvest Croo Robotics specializes in creating innovative robotics solutions that incorporate applied AI technologies to modernize agricultural practices in North America. The company focuses on autonomous farming systems that enhance harvesting efficiency and accuracy, particularly in high-value crops such as strawberries. Harvest Croo Robotics emphasizes the importance of combining agricultural knowledge with cutting-edge technology, ensuring their products are practical and beneficial to farmers. Their key products include robotic harvesters designed to operate autonomously while seamlessly integrating with existing farming operations. The company's strengths are anchored in its ability to innovate rapidly, and its active engagement in industry partnerships and collaborations, positioning it at the forefront of the agricultural robotics market. By pursuing strategic initiatives, including mergers and acquisitions, Harvest Croo Robotics is enhancing its technology portfolio and expanding its market reach within North America, ultimately striving to make farming more efficient and sustainable. **Key Companies in the North America Applied****AI****in Agriculture Market Include** - Harvest Croo Robotics - Monsanto - Granular - Corteva Agriscience - IBM - Taranis - Ag Leader Technology - Trimble - Microsoft - John Deere - Bayer **North America Applied****AI****in Agriculture****Market****Developments** Harvest CROO Robotics, which combines real-time analytics, machine learning, and robotics to alleviate labor shortages in specialty crops, revealed in April 2025 that its AI- and vision-enabled B8 robotic strawberry harvester achieved human-level performance in commercial-scale field trials in Florida. In order to increase resilience to North American corn diseases and support its Granular Insights AI platform for farm management decision support, Corteva Agriscience published research in June 2023 that confirmed gene editing innovations using CRISPR to co-locate multiple disease-resistant genes within single corn hybrids. In order to improve planting, fungicide use, and yield forecasts by several bushels per acre, Corteva introduced AI-driven improvements to Granular Insights in May 2023. These improvements integrated satellite images, connection data streams, and picture recognition. Through its IBM Watson Decision Platform, IBM extended its agricultural analytics offerings in August 2023, implementing AI-based forecasts for crop stress, irrigation, and livestock health on a large scale on American farms.In early 2024, Trimble and Ag-Leader Technology carried on providing AI-enhanced precision mapping services, opening the door for sensor-based variable-rate applications. By mid-2023, John Deere had more than 1.5 million machines linked to its Operations Center, collecting telemetry and providing AI-based insights for yield mapping, weeding, and spraying—all part of the company's continued push toward autonomous farming. Throughout 2023, North American clients embraced Bayer's AI advise modules on crop protection and disease forecasting, even as the company continued to expand its Climate FieldView platform globally. When taken as a whole, these businesses demonstrate tangible, AI-driven implementations in the agricultural industry in North America from January 2023. **North America Applied****AI****in Agriculture Market Segmentation Insights** - **Applied AI in Agriculture Market Technology Outlook** - Machine Learning - Computer Vision - Predictive Analytics - **Applied AI in Agriculture Market Offering Outlook** - Software - AI-as-a-Service - **Applied AI in Agriculture Market Application Outlook** - Drone Analytics - Precision Farming - **Applied AI in Agriculture Market Regional Outlook** - US - Canada ## Market Drivers ### Labor Shortages in Agriculture Labor shortages are increasingly impacting the agricultural sector, prompting a shift towards automation and AI solutions. The applied AI in agriculture market is responding to this challenge by providing technologies that can perform tasks traditionally done by human laborers. For example, AI-powered robots are being utilized for planting, harvesting, and monitoring crops, thereby alleviating the pressure of labor shortages. In North America, it is estimated that the agricultural workforce has declined by 20% over the past decade, which has led to a greater reliance on AI technologies. This trend is likely to continue, further propelling the applied ai-in-agriculture market. ### Technological Advancements in AI The applied AI in agriculture market is experiencing a surge due to rapid technological advancements in artificial intelligence. Innovations such as machine learning algorithms and computer vision are enhancing crop monitoring and yield prediction. For instance, the integration of AI-driven drones and sensors allows farmers to collect real-time data, leading to more informed decision-making. In North America, the market for AI in agriculture is projected to reach approximately $2.6 billion by 2027, reflecting a compound annual growth rate (CAGR) of around 25%. This growth is indicative of the increasing reliance on technology to optimize agricultural practices, thereby driving the applied ai-in-agriculture market forward. ### Increasing Demand for Food Security The growing global population is driving an urgent need for enhanced food security, which is significantly influencing the applied AI in agriculture market. As food demand is expected to increase by 70% by 2050, AI technologies are being leveraged to maximize crop yields and improve food production efficiency. In North America, the application of AI in agriculture is seen as a critical strategy to meet these demands. Farmers are utilizing predictive analytics and AI-driven insights to optimize planting schedules and resource allocation, thereby ensuring a more secure food supply. This increasing focus on food security is likely to sustain growth in the applied ai-in-agriculture market. ### Investment in Agricultural Technology Investment in agricultural technology is a crucial driver for the applied AI in agriculture market. Venture capital and government funding are increasingly directed towards innovative agri-tech startups that focus on AI applications. In North America, investments in agri-tech reached approximately $1.5 billion in 2025, reflecting a growing recognition of the potential of AI to transform agriculture. This influx of capital is fostering research and development, leading to the creation of advanced AI tools that enhance productivity and efficiency. As investment continues to flow into this sector, the applied ai-in-agriculture market is expected to expand significantly. ### Sustainability and Environmental Concerns Sustainability is becoming a pivotal driver in the applied AI in agriculture market. As consumers demand more environmentally friendly practices, farmers are turning to AI solutions to reduce waste and enhance resource efficiency. AI technologies can optimize water usage, minimize pesticide application, and improve soil health, aligning agricultural practices with sustainability goals. In North America, approximately 70% of farmers are reportedly adopting AI technologies to meet these environmental standards. This shift not only addresses consumer preferences but also positions the applied ai-in-agriculture market as a key player in the broader sustainability movement. ## Future Outlook The [Applied AI in Agriculture Market](https://www.marketresearchfuture.com/reports/applied-ai-in-agriculture-market-12168) is projected to grow at a 29.32% CAGR from 2025 to 2035, driven by technological advancements, increased efficiency, and sustainability initiatives. **New opportunities:** - Development of precision agriculture platforms integrating AI analytics. - Investment in autonomous farming equipment for enhanced productivity. - Creation of AI-driven pest management solutions to reduce chemical usage. By 2035, the market is expected to achieve substantial growth, driven by innovation and strategic investments. ## Segment Insights ### By Technology: Machine Learning (Largest) vs. Computer Vision (Fastest-Growing) In the applied AI-in-agriculture market, Machine Learning stands out as the largest segment, capturing a significant share of the overall technology market. Its advanced algorithms enable farmers to optimize various processes, from planting to harvest. Computer Vision follows closely, driven by innovations in image recognition and processing capabilities, leading to substantial growth in recent years. The growth trends in the technology segment are primarily fueled by increasing data availability and the demand for efficiency in agriculture. Predictive Analytics, while crucial, acts as an enabler for other technologies, influencing decision-making and resource allocation. The adoption of these technologies is also bolstered by government initiatives supporting smart farming practices and the integration of AI in various agricultural processes. Technology: Machine Learning (Dominant) vs. Computer Vision (Emerging) Machine Learning is the dominant force in the technology landscape for applied AI in agriculture. Its capacity to learn from data allows farmers to predict outcomes and improve yield. In contrast, Computer Vision, although emerging, is rapidly gaining traction due to its ability to facilitate real-time monitoring of crops and livestock. Together, these technologies are revolutionizing agricultural practices, making them more efficient and data-driven. Machine Learning's established presence provides a solid foundation, while Computer Vision's innovative applications enhance precision agriculture and offer intelligent insights that empower farmers. ### By Offering: Software (Largest) vs. AI-as-a-Service (Fastest-Growing) In the applied ai-in-agriculture market, the software segment holds a significant portion of the market share, reflecting robust adoption among agricultural enterprises. This segment is characterized by its extensive capabilities, providing solutions that enhance productivity, efficiency, and data analysis. Conversely, AI-as-a-Service is rapidly gaining traction, driven by companies seeking flexibility and scalability without hefty upfront investments. This combination positions AI-as-a-Service as a crucial player in the market landscape, appealing especially to smaller farms and agri-tech startups. The growth trends within this segment highlight an increasing reliance on technology to solve complex agricultural problems. Factors driving these developments include the rising need for precision agriculture, improved data collection methodologies, and the integration of Internet of Things (IoT) devices. As farmers and businesses become more adept at utilizing AI, the growth potential for both Software and AI-as-a-Service remains promising, with increasing investments contributing to innovation and service enhancement. Software (Dominant) vs. AI-as-a-Service (Emerging) Software solutions in the applied ai-in-agriculture market are predominantly established, offering comprehensive functionalities that support decision-making, crop management, and resource allocation. This segment's dominance is fueled by various developed tools that integrate seamlessly into existing agricultural systems. On the other hand, AI-as-a-Service presents an emerging alternative, appealing to businesses looking for cost-effective solutions with lower barriers to entry. Its flexibility allows users to access advanced AI capabilities without needing extensive infrastructure, thus making it particularly attractive for firms aiming to innovate rapidly and adapt to changing market demands. Both segments bring unique strengths to the table, addressing diverse needs across the agricultural spectrum. ### By Application: Drone Analytics (Largest) vs. Precision Farming (Fastest-Growing) In the application segment, Drone Analytics currently holds the largest market share among the various solutions available. This technology is becoming increasingly popular among agricultural professionals for its ability to provide real-time data and insights, contributing significantly to decision-making processes on farms. Meanwhile, Precision Farming is the fastest-growing category, gaining traction as more farmers seek to enhance crop yields while minimizing waste through the utilization of advanced technologies. The growth trends in this segment are fueled by the rising need for efficiency and sustainability in farming practices. Innovations in sensor technology, AI algorithms, and data analytics are driving the adoption of these applications. As farmers face challenges related to climate change and crop management, the demand for targeted solutions like Drone Analytics and Precision Farming is expected to continue its upward trajectory, enabling a more data-driven approach to agriculture. Drone Analytics (Dominant) vs. Precision Farming (Emerging) Drone Analytics serves as the dominant force in this segment, offering capabilities such as aerial imagery and mapping that allow farmers to monitor crop health and optimize resource use. It provides a visual understanding of field conditions, enabling timely interventions to maximize agricultural productivity. On the other hand, Precision Farming represents an emerging trend focused on integrating technology with farming practices. This approach uses data from various sources including IoT devices and satellite imagery, to enhance farming operations. The increasing adoption of Artificial Intelligence in Precision Farming is poised to transform traditional agriculture, making it smarter and more efficient. Both segments are crucial for the modern agricultural landscape, with Drone Analytics leading in established market presence and Precision Farming rapidly gaining ground. ## Regional Market Share Analysis ### US : Innovative Solutions Drive Growth The US holds a dominant market share of approximately 84.0% in the applied AI-in-agriculture sector, valued at $650.0 million. Key growth drivers include advancements in precision agriculture technologies, increasing demand for sustainable farming practices, and supportive government initiatives like the USDA's investment in agricultural innovation. Regulatory policies promoting data sharing and environmental sustainability further enhance market potential, while robust infrastructure supports technology deployment across rural areas. ### Canada : Sustainable Practices Gain Traction Canada's market for applied AI in agriculture is valued at $121.31 million, representing about 16.0% of the North American market. Growth is driven by increasing adoption of smart farming technologies and government support for sustainable agricultural practices. The Canadian government has initiated programs to enhance digital agriculture, focusing on data analytics and AI applications. Demand is rising for solutions that improve crop yield and resource management, reflecting a shift towards eco-friendly farming. ## Competitive Benchmarking The applied ai-in-agriculture market in North America is characterized by a dynamic competitive landscape, driven by technological advancements and increasing demand for sustainable agricultural practices. Key players such as Bayer (DE), Corteva Agriscience (US), and John Deere (US) are at the forefront, leveraging innovation and strategic partnerships to enhance their market positioning. Bayer (DE) focuses on integrating AI into its crop protection solutions, while Corteva Agriscience (US) emphasizes digital agriculture tools to optimize yield and resource management. John Deere (US) is enhancing its precision agriculture offerings through advanced data analytics, collectively shaping a competitive environment that prioritizes technological integration and sustainability.The market structure appears moderately fragmented, with several players vying for market share through localized manufacturing and supply chain optimization. Companies are increasingly localizing their operations to better serve regional markets, which enhances responsiveness to local agricultural needs. This strategy not only improves supply chain efficiency but also fosters closer relationships with farmers, thereby strengthening brand loyalty and market presence. In October Bayer (DE) announced a partnership with a leading AI technology firm to develop predictive analytics tools aimed at improving crop yield forecasting. This strategic move is likely to enhance Bayer's product offerings, allowing farmers to make more informed decisions based on real-time data. The integration of AI into Bayer's existing solutions may also position the company as a leader in precision agriculture, potentially increasing its market share. In September Corteva Agriscience (US) launched a new digital platform that utilizes machine learning algorithms to provide tailored agronomic advice to farmers. This initiative is significant as it not only enhances the company's service portfolio but also aligns with the growing trend of personalized agriculture solutions. By leveraging AI, Corteva aims to improve crop management practices, thereby increasing productivity and sustainability in farming operations. In August John Deere (US) expanded its partnership with a tech startup specializing in AI-driven farm management software. This collaboration is expected to enhance John Deere's capabilities in data analytics and machine learning, allowing for more efficient farm operations. The strategic importance of this partnership lies in its potential to create a comprehensive ecosystem that integrates hardware and software solutions, thereby providing farmers with a holistic approach to farm management. As of November the competitive trends in the applied ai-in-agriculture market are increasingly defined by digitalization, sustainability, and the integration of AI technologies. Strategic alliances among key players are shaping the landscape, fostering innovation and enhancing product offerings. The shift from price-based competition to a focus on technological advancement and supply chain reliability is evident, suggesting that future competitive differentiation will hinge on the ability to innovate and adapt to evolving agricultural challenges. ## Recent News & Developments Harvest CROO Robotics, which combines real-time analytics, machine learning, and robotics to alleviate labor shortages in specialty crops, revealed in April 2025 that its AI- and vision-enabled B8 robotic strawberry harvester achieved human-level performance in commercial-scale field trials in Florida. In order to increase resilience to North American corn diseases and support its Granular Insights AI platform for farm management decision support, Corteva Agriscience published research in June 2023 that confirmed gene editing innovations using CRISPR to co-locate multiple disease-resistant genes within single corn hybrids. In order to improve planting, fungicide use, and yield forecasts by several bushels per acre, Corteva introduced AI-driven improvements to Granular Insights in May 2023. These improvements integrated satellite images, connection data streams, and picture recognition. Through its IBM Watson Decision Platform, IBM extended its agricultural analytics offerings in August 2023, implementing AI-based forecasts for crop stress, irrigation, and livestock health on a large scale on American farms.In early 2024, Trimble and Ag-Leader Technology carried on providing AI-enhanced precision mapping services, opening the door for sensor-based variable-rate applications. By mid-2023, John Deere had more than 1.5 million machines linked to its Operations Center, collecting telemetry and providing AI-based insights for yield mapping, weeding, and spraying—all part of the company's continued push toward autonomous farming. Throughout 2023, North American clients embraced Bayer's AI advise modules on crop protection and disease forecasting, even as the company continued to expand its Climate FieldView platform globally. When taken as a whole, these businesses demonstrate tangible, AI-driven implementations in the agricultural industry in North America from January 2023. **North America Applied****AI** ## Report Scope | MARKET SIZE 2024 | 771.31(USD Million) | | --- | --- | | MARKET SIZE 2025 | 997.45(USD Million) | | MARKET SIZE 2035 | 13048.4(USD Million) | | COMPOUND ANNUAL GROWTH RATE (CAGR) | 29.32% (2025 - 2035) | | REPORT COVERAGE | Revenue Forecast, Competitive Landscape, Growth Factors, and Trends | | BASE YEAR | 2024 | | Market Forecast Period | 2025 - 2035 | | Historical Data | 2019 - 2024 | | Market Forecast Units | USD Million | | Key Companies Profiled | Bayer (DE), Corteva Agriscience (US), Syngenta (CH), John Deere (US), AG Leader Technology (US), Trimble (US), Taranis (IL), Farmers Edge (CA), Aker Solutions (NO) | | Segments Covered | Technology, Offering, Application | | Key Market Opportunities | Integration of precision agriculture technologies enhances yield and resource efficiency in the applied ai-in-agriculture market. | | Key Market Dynamics | Technological advancements drive efficiency and sustainability in the applied ai-in-agriculture market across North America. | | Countries Covered | US, Canada | ## Frequently Asked Questions **Q: What is the projected market valuation for the North America applied ai-in-agriculture market by 2035?** A: The projected market valuation is expected to reach 13048.4 USD Million by 2035. **Q: What was the market valuation in 2024 for the North America applied ai-in-agriculture market?** A: The market valuation was 771.31 USD Million in 2024. **Q: What is the expected CAGR for the North America applied ai-in-agriculture market during the forecast period 2025 - 2035?** A: The expected CAGR is 29.32% during the forecast period 2025 - 2035. **Q: Which technology segment is projected to have the highest valuation by 2035?** A: The Computer Vision segment is projected to reach 4000.0 USD Million by 2035. **Q: What are the key players in the North America applied ai-in-agriculture market?** A: Key players include Bayer, Corteva Agriscience, Syngenta, John Deere, and Trimble. **Q: What is the projected valuation for the AI-as-a-Service offering by 2035?** A: The AI-as-a-Service offering is projected to reach 7048.4 USD Million by 2035. **Q: How much is the Precision Farming application segment expected to be valued at by 2035?** A: The Precision Farming application segment is expected to be valued at 9548.4 USD Million by 2035. **Q: What was the valuation of the Machine Learning technology segment in 2024?** A: The Machine Learning technology segment was valued at 200.0 USD Million in 2024. **Q: Which application segment is anticipated to grow significantly in the North America applied ai-in-agriculture market?** A: Drone Analytics is anticipated to grow, reaching 3500.0 USD Million by 2035. **Q: What is the expected growth trend for the software offering in the North America applied ai-in-agriculture market?** A: The software offering is expected to grow, reaching 6000.0 USD Million by 2035. --- *This Markdown endpoint is provided for AI systems and LLM crawlers. 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