×
Request Free Sample ×

Kindly complete the form below to receive a free sample of this Report

Leading companies partner with us for data-driven Insights

clients tt-cursor
Hero Background

Artificial Intelligence In Agriculture Market

ID: MRFR/ICT/20990-HCR
100 Pages
Aarti Dhapte
October 2025

Artificial Intelligence In Agriculture Market Research Report By Type of Application (Crop Monitoring, Livestock Monitoring, Precision Farming, Predictive Analytics, Supply Chain Optimization), By Technology (Computer Vision, Machine Learning, Deep Learning, Big Data Analytics, Robotics), By Application (Crop Production, Livestock Production, Forestry, Aquaculture, Other) and By Regional (North America, Europe, South America, Asia Pacific, Middle East and Africa) - Forecast to 2035

Share:
Download PDF ×

We do not share your information with anyone. However, we may send you emails based on your report interest from time to time. You may contact us at any time to opt-out.

Artificial Intelligence In Agriculture Market Infographic
Purchase Options

Artificial Intelligence In Agriculture Market Summary

As per MRFR analysis, the Artificial Intelligence In Agriculture Market was estimated at 4.856 USD Billion in 2024. The Artificial Intelligence In Agriculture industry is projected to grow from 5.821 USD Billion in 2025 to 35.63 USD Billion by 2035, exhibiting a compound annual growth rate (CAGR) of 19.86 during the forecast period 2025 - 2035.

Key Market Trends & Highlights

The Artificial Intelligence in Agriculture Market is poised for substantial growth driven by technological advancements and increasing demand for food security.

  • North America remains the largest market for AI in agriculture, driven by advanced technological infrastructure and investment.
  • The Asia-Pacific region is emerging as the fastest-growing market, fueled by rapid adoption of innovative agricultural practices.
  • Crop monitoring is the largest segment, while precision farming is experiencing the fastest growth due to its efficiency and effectiveness.
  • Key market drivers include rising demand for food security and government initiatives supporting technological advancements in agriculture.

Market Size & Forecast

2024 Market Size 4.856 (USD Billion)
2035 Market Size 35.63 (USD Billion)
CAGR (2025 - 2035) 19.86%

Major Players

Bayer (DE), Corteva (US), Syngenta (CH), IBM (US), John Deere (US), Trimble (US), AG Leader Technology (US), Taranis (IL), Granular (US)

Artificial Intelligence In Agriculture Market Trends

The Artificial Intelligence In Agriculture Market is currently experiencing a transformative phase, driven by advancements in technology and the increasing need for sustainable farming practices. As agricultural stakeholders seek to enhance productivity and efficiency, AI applications such as precision farming, crop monitoring, and predictive analytics are gaining traction. These innovations not only optimize resource utilization but also contribute to improved crop yields and reduced environmental impact. The integration of AI technologies is reshaping traditional farming methods, enabling farmers to make data-driven decisions that align with modern agricultural demands. Moreover, the market appears to be influenced by a growing awareness of food security and the necessity for innovative solutions to address global challenges. The adoption of AI in agriculture seems to facilitate better management of agricultural resources, thereby enhancing resilience against climate change and other external pressures. As the industry evolves, collaboration between technology providers and agricultural experts is likely to foster further advancements, ensuring that the Artificial Intelligence In Agriculture Market remains at the forefront of agricultural innovation. This synergy may lead to the development of more sophisticated tools and platforms that cater to the diverse needs of farmers worldwide.

Precision Agriculture Adoption

The trend towards precision agriculture is becoming increasingly prominent within the Artificial Intelligence In Agriculture Market. This approach utilizes AI technologies to analyze data from various sources, allowing farmers to make informed decisions regarding planting, irrigation, and fertilization. By optimizing these processes, farmers can enhance crop yields while minimizing waste and resource consumption.

AI-Driven Crop Monitoring

AI-driven crop monitoring is emerging as a vital trend in the Artificial Intelligence In Agriculture Market. Utilizing drones and satellite imagery, farmers can monitor crop health in real-time, identifying issues such as pest infestations or nutrient deficiencies early on. This proactive approach enables timely interventions, ultimately leading to healthier crops and improved productivity.

Predictive Analytics for Yield Forecasting

The use of predictive analytics for yield forecasting is gaining momentum in the Artificial Intelligence In Agriculture Market. By analyzing historical data and current environmental conditions, AI systems can provide accurate forecasts of crop yields. This capability allows farmers to plan better, manage resources effectively, and make strategic decisions that enhance overall agricultural productivity.

Artificial Intelligence In Agriculture Market Drivers

Rising Demand for Food Security

The increasing global population necessitates enhanced food production, thereby driving the Artificial Intelligence In Agriculture Market. As the demand for food escalates, farmers are compelled to adopt innovative technologies to optimize crop yields. AI applications, such as predictive analytics and machine learning, enable farmers to make data-driven decisions, improving efficiency and sustainability. According to recent estimates, the agricultural sector must increase food production by approximately 70% by 2050 to meet the needs of the growing population. This urgency propels the integration of AI technologies, which can analyze vast datasets to identify trends and optimize resource allocation, ultimately contributing to food security.

Technological Advancements in AI

The rapid evolution of artificial intelligence technologies significantly influences the Artificial Intelligence In Agriculture Market. Innovations in machine learning, computer vision, and robotics are transforming traditional farming practices. For instance, AI-powered drones and sensors facilitate real-time monitoring of crop health, soil conditions, and weather patterns. These advancements allow for precise interventions, reducing waste and enhancing productivity. The market for AI in agriculture is projected to reach substantial figures, with estimates suggesting a compound annual growth rate of over 25% in the coming years. This growth is indicative of the increasing reliance on technology to address agricultural challenges.

Government Initiatives and Support

Government policies and initiatives play a pivotal role in shaping the Artificial Intelligence In Agriculture Market. Many governments are recognizing the potential of AI to enhance agricultural productivity and are implementing supportive measures, such as funding research and development projects. These initiatives often include grants, subsidies, and tax incentives aimed at encouraging the adoption of AI technologies among farmers. As a result, the market is witnessing increased investment in AI-driven solutions, which are expected to improve efficiency and competitiveness in the agricultural sector. Such governmental support is likely to foster innovation and accelerate the integration of AI in agriculture.

Sustainability and Environmental Concerns

Growing awareness of environmental issues drives the adoption of sustainable practices within the Artificial Intelligence In Agriculture Market. Farmers are increasingly seeking methods to reduce their ecological footprint while maintaining productivity. AI technologies assist in optimizing resource use, such as water and fertilizers, thereby minimizing waste and environmental impact. For example, precision irrigation systems powered by AI can significantly reduce water consumption, which is crucial in regions facing water scarcity. The emphasis on sustainability is likely to propel investments in AI solutions that promote eco-friendly farming practices, aligning agricultural productivity with environmental stewardship.

Increasing Investment in Agri-Tech Startups

The surge in investment towards agri-tech startups is a notable driver of the Artificial Intelligence In Agriculture Market. Venture capitalists and investors are increasingly recognizing the potential of AI to revolutionize agriculture. This influx of capital enables startups to develop innovative solutions that address various agricultural challenges, from crop management to supply chain optimization. Reports indicate that investments in agri-tech have reached billions, reflecting a growing confidence in the sector's future. As these startups introduce cutting-edge technologies, they contribute to the overall growth of the AI market in agriculture, fostering a competitive landscape that benefits farmers and consumers alike.

Market Segment Insights

By Type of Application: Crop Monitoring (Largest) vs. Precision Farming (Fastest-Growing)

In the Artificial Intelligence in Agriculture Market, the segment of Crop Monitoring holds the largest share, as it is fundamental to farmers seeking to optimize yields and reduce losses due to pests and diseases. This segment benefits from advancements in sensor technology and data analytics, enabling real-time monitoring of crop health and environmental conditions. Conversely, Precision Farming, while currently smaller in market share, is recognized as the fastest-growing application due to its ability to integrate various data sources and automate farming processes, appealing to modern agricultural practices.

Crop Monitoring (Dominant) vs. Precision Farming (Emerging)

The Crop Monitoring segment is characterized by its reliance on advanced technologies such as drones, IoT sensors, and machine learning algorithms to assess crop conditions and recommend actionable insights. It is a mature application widely adopted among farmers and agronomists, contributing significantly to yield optimization and resource management. On the other hand, Precision Farming, as an emerging segment, focuses on smart farming techniques to enhance productivity through data-driven decisions. It encompasses a variety of technologies, including GPS-guided equipment and variable rate technology, catering to the growing demand for efficient land use and sustainability in agriculture.

By Technology: Machine Learning (Largest) vs. Deep Learning (Fastest-Growing)

The Artificial Intelligence In Agriculture Market showcases a diverse array of technology-driven solutions, with Machine Learning currently holding the largest market share. Its widespread application in enhancing crop yields, predicting weather patterns, and enabling precision farming techniques makes it indispensable for modern agricultural practices. Deep Learning, on the other hand, is rapidly gaining traction as an innovative force in this sector, due to its ability to analyze complex datasets and improve decision-making processes. As the demand for smart farming solutions intensifies, emerging technologies like Deep Learning are becoming invaluable, with significant growth potential driven by advancements in neural networks and data processing capabilities. This trend is further fueled by the increasing reliance on automation in agriculture and the need for better resource management. As more stakeholders recognize the benefits of AI technologies, the market is projected to expand significantly in the coming years, highlighting the critical role of these technologies in shaping the future of agriculture.

Technology: Machine Learning (Dominant) vs. Robotics (Emerging)

Machine Learning stands at the forefront of the Artificial Intelligence In Agriculture Market, playing a pivotal role in optimizing agricultural operations. Its capability to learn from vast amounts of data allows for customized and predictive analytics, which enhances efficiency and productivity. Conversely, Robotics is emerging as a complementary technology, equipped with autonomous machinery that performs tasks ranging from planting to harvesting. The integration of AI with robotics is revolutionizing farm operations, leading to better labor management and precision in fieldwork. While Machine Learning is widely recognized and implemented, the budding development in Robotics points toward an exciting future where automated processes will further transform agricultural methodologies, making them more efficient and sustainable.

By Application: Crop Production (Largest) vs. Livestock Production (Fastest-Growing)

In the Artificial Intelligence In Agriculture Market, the application segment is dominated by crop production, which plays a crucial role in enhancing yield through precision farming techniques and data-driven decision-making. Livestock production is gaining momentum, focusing on improving animal health and productivity through AI-driven monitoring solutions. Together, these segments represent a significant portion of the market, showcasing the diverse applications of AI in agricultural practices.

Crop Production (Dominant) vs. Livestock Production (Emerging)

Crop production is characterized by its robust integration of AI technologies to optimize yield and resource usage, utilizing tools like drones, imaging systems, and predictive analytics. This segment leads the market with widespread adoption among farmers seeking to maximize efficiency and sustainability practices. In contrast, livestock production stands as an emerging segment, driven by the need for enhanced livestock management. Through AI-based health monitoring, feed optimization, and reproduction management, this sector is rapidly evolving, with producers increasingly relying on technology to enhance productivity and animal welfare.

Get more detailed insights about Artificial Intelligence In Agriculture Market

Regional Insights

North America : Innovation and Investment Hub

North America is the largest market for Artificial Intelligence in Agriculture, holding approximately 45% of the global share. The region benefits from advanced technological infrastructure, significant investment in agri-tech startups, and supportive government policies aimed at enhancing agricultural productivity. The increasing demand for precision farming and sustainable practices further drives market growth, with regulations promoting the adoption of AI technologies in farming. The United States and Canada are the leading countries in this sector, with major players like John Deere, IBM, and Corteva leading the charge. The competitive landscape is characterized by a mix of established corporations and innovative startups, all vying to leverage AI for improved crop yields and resource management. The presence of key players ensures a robust ecosystem for AI development in agriculture, fostering collaboration and innovation.

Europe : Sustainable Agriculture Focus

Europe is witnessing rapid growth in the Artificial Intelligence in Agriculture market, accounting for approximately 30% of the global share. The region's focus on sustainable agricultural practices and environmental regulations drives demand for AI solutions that enhance efficiency and reduce waste. Initiatives from the European Union, such as the Green Deal, promote the integration of AI technologies in farming, creating a favorable regulatory environment for innovation. Leading countries in this market include Germany, France, and the Netherlands, where companies like Bayer and Syngenta are at the forefront of AI adoption. The competitive landscape is marked by collaboration between tech firms and agricultural stakeholders, fostering innovation. The presence of key players and a strong emphasis on sustainability position Europe as a significant player in the AI agriculture market, driving advancements in precision farming and crop management.

Asia-Pacific : Rapid Growth and Adoption

Asia-Pacific is rapidly emerging as a significant player in the Artificial Intelligence in Agriculture market, holding around 20% of the global share. The region's diverse agricultural landscape and increasing population drive the demand for innovative farming solutions. Governments are actively promoting the adoption of AI technologies to enhance food security and agricultural productivity, with various initiatives aimed at modernizing farming practices and improving efficiency. Countries like China, India, and Australia are leading the charge, with a growing number of startups and established companies investing in AI-driven agricultural solutions. The competitive landscape is evolving, with local players collaborating with global tech firms to develop tailored solutions for regional challenges. This dynamic environment fosters innovation and positions Asia-Pacific as a key market for AI in agriculture, with significant growth potential in the coming years.

Middle East and Africa : Resource-Rich Frontier

The Middle East and Africa region is gradually emerging in the Artificial Intelligence in Agriculture market, accounting for approximately 5% of the global share. The region faces unique agricultural challenges, including water scarcity and arid climates, which drive the need for innovative AI solutions. Governments are increasingly recognizing the potential of AI to enhance agricultural productivity and sustainability, leading to supportive policies and investments in agri-tech initiatives. Countries like South Africa, Kenya, and the UAE are at the forefront of AI adoption in agriculture, with a growing number of startups and initiatives aimed at leveraging technology for improved farming practices. The competitive landscape is characterized by collaborations between local and international players, fostering innovation and knowledge transfer. As the region continues to invest in AI technologies, it is poised for significant growth in the agricultural sector, addressing both local and global food security challenges.

Artificial Intelligence In Agriculture Market Regional Image

Key Players and Competitive Insights

The Artificial Intelligence in Agriculture Market is currently characterized by a dynamic competitive landscape, driven by technological advancements and the increasing need for sustainable agricultural practices. Key players such as Bayer (DE), Corteva (US), and John Deere (US) are strategically positioning themselves through innovation and partnerships, which collectively enhance their market presence. Bayer (DE) focuses on integrating AI with biotechnology to optimize crop yields, while Corteva (US) emphasizes digital farming solutions that leverage AI for precision agriculture. John Deere (US) is advancing its autonomous machinery capabilities, indicating a strong commitment to automation and efficiency in farming operations.

In terms of business tactics, companies are increasingly localizing manufacturing and optimizing supply chains to enhance responsiveness to market demands. The competitive structure of the market appears moderately fragmented, with several players vying for market share. However, the influence of major companies is substantial, as they set industry standards and drive technological innovation, thereby shaping the overall market dynamics.

In August 2025, Bayer (DE) announced a partnership with a leading AI firm to develop predictive analytics tools aimed at improving pest management strategies. This collaboration is likely to enhance Bayer's product offerings, allowing farmers to make data-driven decisions that could significantly reduce crop losses. The strategic importance of this move lies in its potential to position Bayer as a leader in sustainable agricultural practices, aligning with global trends towards environmental responsibility.

In September 2025, Corteva (US) launched a new AI-driven platform designed to provide real-time insights into soil health and crop performance. This initiative not only reinforces Corteva's commitment to innovation but also addresses the growing demand for data-centric farming solutions. By offering farmers actionable insights, Corteva is likely to strengthen its market position and foster long-term customer loyalty.

In October 2025, John Deere (US) unveiled an advanced AI system that enhances the efficiency of its autonomous tractors. This system utilizes machine learning algorithms to optimize field operations, potentially reducing fuel consumption and operational costs for farmers. The introduction of this technology underscores John Deere's focus on automation and efficiency, which are critical in an increasingly competitive market.

As of October 2025, the most prominent trends shaping the competitive landscape include digitalization, sustainability, and the integration of AI technologies. Strategic alliances among key players are fostering innovation and enhancing product offerings, which is crucial in a market that is rapidly evolving. Looking ahead, competitive differentiation is expected to shift from traditional price-based competition to a focus on innovation, technological advancements, and supply chain reliability, as companies strive to meet the demands of a more discerning agricultural sector.

Key Companies in the Artificial Intelligence In Agriculture Market market include

Industry Developments

  • Q2 2024: John Deere launches new AI-powered See & Spray Ultimate technology for row crops John Deere announced the commercial launch of its See & Spray Ultimate system, which uses artificial intelligence and machine learning to detect and target weeds in row crops, aiming to reduce herbicide use and improve yields.
  • Q2 2024: CNH Industrial acquires Augmenta to accelerate AI-driven precision agriculture solutions CNH Industrial completed the acquisition of Augmenta, a company specializing in AI-based sensor technology for real-time variable rate application, to enhance its digital farming portfolio.
  • Q2 2024: Ceres Imaging raises $23 million in Series C funding to expand AI-powered crop analytics Ceres Imaging, a provider of aerial imagery analytics for agriculture, secured $23 million in Series C funding to scale its AI-driven crop monitoring and decision support tools.
  • Q3 2024: Agtonomy partners with Yamaha Motor to develop autonomous, AI-driven tractors for specialty crops Agtonomy announced a partnership with Yamaha Motor to co-develop autonomous tractors equipped with AI for specialty crop operations, aiming to address labor shortages and improve efficiency.
  • Q3 2024: IBM and Bayer announce strategic partnership to deploy AI-powered climate-smart agriculture solutions IBM and Bayer entered a multi-year partnership to integrate IBM's AI and weather analytics with Bayer's digital farming platform, targeting improved climate resilience and productivity for farmers.
  • Q3 2024: Ecorobotix secures €40 million in Series D funding to scale AI-based precision spraying robots Swiss agtech company Ecorobotix raised €40 million in Series D funding to accelerate the commercialization of its AI-powered precision spraying robots for sustainable agriculture.
  • Q4 2024: Corteva Agriscience acquires AI startup Sencrop to boost digital agriculture capabilities Corteva Agriscience acquired Sencrop, a French agtech startup specializing in AI-driven weather and crop monitoring, to strengthen its digital agriculture offerings.
  • Q4 2024: Blue River Technology opens new AI research facility in California Blue River Technology, a subsidiary of John Deere, inaugurated a new research facility focused on advancing artificial intelligence applications in agricultural robotics and automation.
  • Q1 2025: Taranis raises $30 million in Series C funding to expand AI-powered crop intelligence platform Taranis, an agtech company specializing in AI-driven aerial crop scouting, closed a $30 million Series C funding round to expand its platform and global reach.
  • Q1 2025: Trimble announces partnership with Microsoft to integrate AI into farm management software Trimble and Microsoft formed a partnership to embed advanced AI capabilities into Trimble's farm management software, aiming to enhance decision-making and operational efficiency for farmers.
  • Q2 2025: XAG launches new generation of AI-powered agricultural drones for precision spraying Chinese agtech company XAG introduced its latest AI-enabled agricultural drones designed for precision spraying and crop monitoring, targeting improved efficiency and reduced chemical use.
  • Q2 2025: BASF Digital Farming appoints new CEO to drive AI innovation in agriculture BASF Digital Farming announced the appointment of a new CEO, emphasizing a strategic focus on accelerating artificial intelligence innovation in its digital agriculture business.

Future Outlook

Artificial Intelligence In Agriculture Market Future Outlook

The Artificial Intelligence in Agriculture Market is projected to grow at a 19.86% CAGR from 2024 to 2035, driven by advancements in precision farming, data analytics, and automation technologies.

New opportunities lie in:

  • Development of AI-driven pest management solutions
  • Integration of IoT with AI for real-time crop monitoring
  • Creation of predictive analytics platforms for yield forecasting

By 2035, the market is expected to be robust, driven by innovative AI applications and increased adoption across the agricultural sector.

Market Segmentation

Artificial Intelligence In Agriculture Market Technology Outlook

  • Computer Vision
  • Machine Learning
  • Deep Learning
  • Big Data Analytics
  • Robotics

Artificial Intelligence In Agriculture Market Application Outlook

  • Crop Production
  • Livestock Production
  • Forestry
  • Aquaculture
  • Other

Artificial Intelligence In Agriculture Market Type of Application Outlook

  • Crop Monitoring
  • Livestock Monitoring
  • Precision Farming
  • Predictive Analytics
  • Supply Chain Optimization

Report Scope

MARKET SIZE 20244.856(USD Billion)
MARKET SIZE 20255.821(USD Billion)
MARKET SIZE 203535.63(USD Billion)
COMPOUND ANNUAL GROWTH RATE (CAGR)19.86% (2024 - 2035)
REPORT COVERAGERevenue Forecast, Competitive Landscape, Growth Factors, and Trends
BASE YEAR2024
Market Forecast Period2025 - 2035
Historical Data2019 - 2024
Market Forecast UnitsUSD Billion
Key Companies ProfiledMarket analysis in progress
Segments CoveredMarket segmentation analysis in progress
Key Market OpportunitiesIntegration of precision agriculture technologies enhances yield and resource efficiency in the Artificial Intelligence In Agriculture Market.
Key Market DynamicsRising adoption of precision agriculture technologies drives demand for Artificial Intelligence solutions in farming practices.
Countries CoveredNorth America, Europe, APAC, South America, MEA

Leave a Comment

FAQs

What is the projected market valuation of Artificial Intelligence in Agriculture by 2035?

The projected market valuation for Artificial Intelligence in Agriculture is expected to reach 35.63 USD Billion by 2035.

What was the market valuation of Artificial Intelligence in Agriculture in 2024?

The overall market valuation for Artificial Intelligence in Agriculture was 4.856 USD Billion in 2024.

What is the expected CAGR for the Artificial Intelligence in Agriculture market from 2025 to 2035?

The expected CAGR for the Artificial Intelligence in Agriculture market during the forecast period 2025 - 2035 is 19.86%.

Which companies are considered key players in the Artificial Intelligence in Agriculture market?

Key players in the market include Bayer, Corteva, Syngenta, IBM, John Deere, Trimble, AG Leader Technology, Taranis, and Granular.

What are the main applications of Artificial Intelligence in Agriculture?

Main applications include Crop Production, Livestock Production, Forestry, Aquaculture, and others, with Crop Production valued at 10.5 USD Billion by 2035.

How does Precision Farming contribute to the market valuation?

Precision Farming is projected to reach a valuation of 10.0 USD Billion by 2035, indicating its substantial contribution to the market.

What technologies are driving the Artificial Intelligence in Agriculture market?

Driving technologies include Machine Learning, Computer Vision, Robotics, Big Data Analytics, and Deep Learning, with Machine Learning expected to reach 9.1 USD Billion by 2035.

What is the valuation of Crop Monitoring in the market?

Crop Monitoring is projected to reach a valuation of 5.5 USD Billion by 2035, reflecting its importance in the sector.

How does Supply Chain Optimization fit into the market landscape?

Supply Chain Optimization is expected to reach 8.63 USD Billion by 2035, highlighting its role in enhancing agricultural efficiency.

What is the future outlook for Livestock Monitoring in the Artificial Intelligence in Agriculture market?

Livestock Monitoring is projected to grow to 4.0 USD Billion by 2035, indicating a positive future outlook for this application.

Download Free Sample

Kindly complete the form below to receive a free sample of this Report

Compare Licence

×
Features License Type
Single User Multiuser License Enterprise User
Price $4,950 $5,950 $7,250
Maximum User Access Limit 1 User Upto 10 Users Unrestricted Access Throughout the Organization
Free Customization
Direct Access to Analyst
Deliverable Format
Platform Access
Discount on Next Purchase 10% 15% 15%
Printable Versions