Generative AI In Agriculture Market By Crop Type (Wheat, Rice, Corn, Vegetables, And Others), By Application (Precision Farming, Livestock Management, Crop Management, And Others), By Technology (Deep Learning, Computer Vision, Machine Learning, And Robotics), By Region And Companies - Industry Segment Outlook, Market Assessment, Competition Scenario, Trends And Forecast 2023-2032
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This report was compiled by Correspondence Linkedin | Detailed Market research Methodology Our methodology involves a mix of primary research, including interviews with leading mental health experts, and secondary research from reputable medical journals and databases. View Detailed Methodology Page
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Report Overview
The Global Generative AI in Agriculture Market size is expected to be worth around USD 1083.9 Mn by 2032 from USD 125 Mn in 2022, growing at a CAGR of 24.8% during the forecast period from 2023 to 2032.
The surge in demand for new advanced technologies and the emergence of the agricultural industry are some of the main driving factors for the generative use of artificial intelligence in the agricultural market. The agricultural market is undergoing a substantial change, with a growing emphasis on sustainability and efficacy.
GenAI is making a significant impact on the industry as it includes training machines to develop and produce data. By using GenAI, farmers can boost their crop yields by minimizing environmental impact and adopting sustainable farming practices.
Generative AI is a new and latest technology that uses data and many algorithms to understand, learn, forecast, and produce new content. GenAI in agriculture has the capability to transform farming practices by offering crop growth, soil conditions, and weather conditions. GenAI helps farmers increase resource allocations, decrease waste, and boost productivity.
It uses ML algorithms to examine a large amount of data. This data is then utilized to develop models that can produce new content like images, videos, and text. It also helps farmers forecast crop yield and growth, recognize potential disease outbreaks, and boost irrigation and fertilization methods.
India holds the second-largest agricultural land all over the world, providing employment for about half of the country’s population. According to the IBEF report published in August 2023, the food processing industry in India will account for 32% of the country’s total food market, which is one of the largest sectors in India and fifth in position with regards to production, consumption, and exports. The food grain industry in India will account for 330.5 million metric tons in 2022–2023.
In terms of the production of food grains, fruits, and vegetables, India is the second-largest producer and the second-largest exporter of sugar. A total of 521.27 LMT of rice has been projected for procurement for future KMS 2023–2024, up from 496 LMT produced during the last KMS 2022–2023.
In July 2022 to June 2023, India’s horticulture result is anticipated to account for a record of 350.87 million metric tons as production of fruits, vegetables, spices, and plantations of crops has drastically risen. Moreover, in October 2022, PM Mr. Narendra Modi inaugurated PM Kisan Samman Sammelan 2022 and released PM- Kisan funds worth Rs. 16,000 crores, which is USD 1.93 billion.
There are several advantages to implementing GenAI in agriculture, such as optimizing crop yield and quality, decreasing waste, and minimizing environmental impact. It also helps in increasing resource allocation, which consists of water and fertilizers.
Gen AI aids in enhancing disease identification and management. This technology also decreases risk and augments profitability. The demand for GenAI in agriculture will increase due to its surge in sustainability and high requirements in agriculture and the food industry, which will help in market expansion in the coming years.
Key Takeaways
- Market Value: The Generative AI in Agriculture Market is projected to reach USD 1083.9 million by 2032, exhibiting a robust CAGR of 24.8% from 2023 to 2032.
- Dominant Segments:
- Crop Type Analysis: Wheat leads with 36.7% market share, followed by rice, corn, vegetables, and other crop types, highlighting the importance of generative AI technologies in optimizing yields across diverse agricultural landscapes.
- Application Analysis: Precision farming dominates with a 35.4% market share, emphasizing the growing need for efficient and sustainable agricultural practices. Other critical applications include livestock management, crop management, soil analysis, and various emerging uses.
- Technology Analysis: Deep Learning holds the largest share at 37.2%, showcasing its efficacy in processing complex agricultural data. Computer Vision, Machine Learning, NLP, and Robotics also play vital roles in transforming farming operations.
- End-User Industry Analysis: Farmers represent the primary end-users, accounting for 42.3% of the market, followed by Agriculture Technology Companies, Agriculture Consultants, Government Agencies, and Research Institutions.
- Regional Dynamics: North America dominates with a 47.6% market share, driven by advanced technology adoption and robust agricultural practices. Other regions, including Europe, also contribute significantly to market growth.
- Key Players: Major players such as IBM Corp., Microsoft Corp., John Deere, and The Climate Corporation (a subsidiary of Bayer) lead the market, driving innovation and adoption of generative AI technologies in agriculture.
- Analyst Viewpoint: Analysts anticipate significant growth opportunities in Generative AI in Agriculture, fueled by increasing demand for precision farming, advancements in AI technologies, and the need for sustainable food production.
- Growth Opportunities: Opportunities lie in expanding applications of generative AI across different crop types, enhancing precision farming techniques, leveraging advanced technologies like Deep Learning and Robotics, and fostering collaboration between stakeholders to drive innovation and sustainability in agriculture.
Driving Factors
Automation and Efficiency Drives Market Growth
The integration of Generative AI into agriculture is revolutionizing how farming tasks are performed, leading to significant enhancements in automation and efficiency. This innovative technology facilitates the automation of critical agricultural operations such as crop monitoring, yield prediction, and pest detection. By utilizing AI algorithms, farmers are empowered to make informed, data-driven decisions that optimize crop yields and improve resource utilization. This shift not only contributes to more sustainable and efficient food production but also aligns with the broader objectives of enhancing operational productivity across the agricultural sector.
In November 2022, a notable advancement was made by DJI Agriculture with the launch of the Mavic 3 Multispectral model. This drone is designed to capture rapid, detailed images of crop growth, aiding in the increased production and quality of crops globally. It exemplifies how technological innovations are providing farmers with tools to reduce costs and maximize income, underscoring the pivotal role of automation and efficiency in the growth of the Generative AI in Agriculture Market. This progression towards more automated agricultural practices signals a transformative period where efficiency and technology converge to meet the demands of modern food production.
Precision Farming Catalyzes Market Expansion
Precision farming stands as a cornerstone in the evolution of agricultural practices, enabled by the integration of Generative AI with cutting-edge technologies such as the Internet of Things (IoT), drones, and satellite imagery. This synergy facilitates a revolutionized approach to farming, offering real-time, detailed analyses of soil conditions, moisture levels, and crop health. Such precise data enables farmers to tailor their practices to the exact needs of their crops, significantly optimizing resource usage and yields.
The ability to apply water, fertilizers, and pesticides with pinpoint accuracy not only minimizes waste but also contributes to environmental sustainability. This targeted approach ensures that resources are utilized efficiently, supporting the global push towards more sustainable agricultural practices. As precision farming becomes more prevalent, it serves as a critical driver for the Generative AI in Agriculture Market, showcasing the potential of technology to reshape traditional farming into a more efficient, productive, and environmentally friendly endeavor.
Technological Advancements Propel Market Forward
Continuous technological advancements in AI and machine learning are at the forefront of driving the Generative AI in Agriculture Market towards new heights. These advancements are pivotal in developing more sophisticated and accurate AI models that can process vast amounts of agricultural data. The insights and predictions generated from this data are invaluable, offering precise guidance for addressing the multifaceted challenges faced in agriculture today.
This evolution of AI technology enhances decision-making processes, enabling more effective solutions to emerge for increasing crop yields, managing resources, and mitigating risks associated with farming. The ripple effects of these technological advancements are widespread, influencing not just the immediate area of agriculture but also the broader ecosystem of food production and supply chain management. As AI and machine learning technologies continue to evolve, their role in transforming agriculture into a more data-driven, efficient, and sustainable industry becomes increasingly significant, marking a new era of growth and innovation in the market.
Restraining Factors
High Implementation Costs Restrains Market Growth
The deployment of generative AI technologies in the field of agriculture comes with high upfront costs. This includes the need for advanced hardware, sophisticated software solutions, sensors, and comprehensive data collection systems. For small-scale farmers and agricultural operations in resource-limited regions, these costs can be a significant barrier.
The financial burden associated with adopting these advanced technologies restricts their accessibility and widespread implementation. Consequently, the market's expansion is limited, as a large segment of potential users finds it challenging to leverage these innovations. This financial hurdle not only affects the adoption rate but also influences the pace at which the generative AI in Agriculture Market can grow, particularly in under-resourced areas.
Data Privacy Concerns Inhibit Market Growth
Data privacy and security emerge as major concerns in the adoption of AI technologies within the agricultural sector. The collection, processing, and analysis of sensitive agricultural data introduce risks related to unauthorized access and misuse. Ensuring robust data protection measures are in place is essential for maintaining trust among stakeholders and complying with regulatory standards.
However, the complexities and costs associated with securing agricultural data can deter farmers and agricultural businesses from adopting generative AI solutions. These concerns about data privacy not only challenge the market's expansion by limiting user trust but also impose additional operational challenges for providers of AI technologies. The need for enhanced security measures and the potential for regulatory scrutiny add layers of complexity, hindering the broader adoption and growth of generative AI in the agriculture market.
Crop Type Analysis
Wheat Leads with 36.7% Market Domination
In the Generative AI in Agriculture Market, crop type segmentation provides insights into the application of AI technologies across different types of crops. Wheat emerges as the dominant sub-segment, accounting for 36.7% of the market. This significant share can be attributed to wheat's essential role in global food security and the increasing demand for sustainable and efficient wheat production practices. Generative AI technologies are utilized to optimize wheat yields, enhance pest and disease management, and improve resource use efficiency, addressing the challenges of climate change and population growth.
Other notable segments include rice, corn, vegetables, and other crop types. Rice and corn, being staple foods for a large portion of the world's population, also see substantial investments in AI to increase production efficiency and sustainability. The vegetable segment benefits from AI in precision agriculture practices, such as yield optimization and disease detection, catering to the rising consumer demand for fresh and high-quality produce.
The "other crop types" segment encompasses a broad range of crops, each presenting unique challenges and opportunities for the application of generative AI technologies. This diversity highlights the market's potential for growth and innovation, driven by the need for customized AI solutions across different agricultural contexts.
The dominance of wheat in the Generative AI in Agriculture Market is indicative of the sector's focus on major staple crops. However, the inclusion and significance of other crop types underscore the versatility and expansive potential of generative AI technologies in agriculture. These technologies offer solutions tailored to the specific needs of different crops, enhancing overall market growth through diversified applications and innovations.
Application Analysis
Precision Farming Leads Generative AI in Agriculture Market with 35.4% Dominance
Within the Generative AI in Agriculture Market, application-based segmentation sheds light on the various uses of AI technologies in farming operations. Precision farming stands out as the dominant sub-segment, holding a 35.4% share of the market. This dominance is driven by the growing need for more efficient and sustainable agricultural practices. Precision farming leverages AI to analyze vast amounts of data from various sources, such as soil sensors, drones, and satellites, to make informed decisions on irrigation, fertilization, and pest management. By optimizing these aspects of agriculture, precision farming significantly enhances crop yields, reduces resource waste, and minimizes environmental impact.
Other critical segments include livestock management, crop management, soil analysis, and other applications. Livestock management uses AI for monitoring animal health and behavior, improving livestock productivity and welfare. Crop management benefits from AI in detecting diseases and pests early, allowing for timely interventions. Soil analysis, enhanced by AI, provides detailed information on soil health and nutrient levels, informing better soil management practices. The "other applications" segment encompasses a wide range of emerging AI uses in agriculture, from greenhouse automation to supply chain optimization, reflecting the technology's adaptability and potential for innovation.
The prominence of precision farming as the dominant application of Generative AI in Agriculture underscores the sector's shift towards more data-driven and efficient farming practices. This shift is essential in meeting the increasing global food demand sustainably. Meanwhile, the importance of other segments, such as livestock management and soil analysis, illustrates the comprehensive role of AI in transforming all aspects of agriculture. The diversity in applications highlights the vast potential of generative AI to address various agricultural challenges, promoting growth and innovation within the market.
Technology Analysis
Deep Learning Leads Generative AI in Agriculture Tech Market with 37.2% Dominance
In the Generative AI in Agriculture Market, technology segmentation underscores the foundational role of various AI technologies in transforming agricultural practices. Deep Learning emerges as the dominant technology, accounting for 37.2% of the market. This preeminence is attributed to deep learning's exceptional ability to process and analyze vast amounts of unstructured data, making it invaluable for applications like image recognition in pest detection and crop health monitoring. By enabling more accurate and efficient analyses, deep learning technologies significantly enhance decision-making processes in agriculture, leading to improved yields and resource management.
Other significant technologies include Computer Vision, Machine Learning, Natural Language Processing (NLP), and Robotics. Computer Vision is pivotal in automating tasks such as crop monitoring and disease identification, leveraging image and video data to deliver precise insights.
Machine Learning underpins various predictive models in agriculture, from yield prediction to climate impact assessments, facilitating a proactive approach to farming. NLP finds its utility in aggregating and interpreting vast datasets, including research papers and market reports, to inform better agricultural practices. Robotics, meanwhile, plays a crucial role in automating physical tasks like harvesting, planting, and weeding, directly impacting labor efficiency and precision.
Deep Learning's dominance in the market underscores the high value placed on technologies capable of processing complex, voluminous datasets to extract actionable insights. Concurrently, the roles of Computer Vision, Machine Learning, NLP, and Robotics highlight the multifaceted nature of technological advancements in agriculture, each contributing uniquely to increasing efficiency, sustainability, and productivity in the sector.
End-User Industry Analysis
Farmers Lead Generative AI Adoption in Agriculture Sector with 42.3% Dominance
The Generative AI in Agriculture Market is also analyzed based on the end-user industry, revealing the primary beneficiaries and users of these technologies. Farmers stand out as the dominant end-user group, representing 42.3% of the market. This dominance underscores the direct impact of generative AI technologies on improving agricultural productivity and sustainability at the ground level.
Farmers leverage AI for a variety of purposes, including optimizing planting schedules, improving pest and disease management, and enhancing crop yields through precision farming techniques. The adoption of AI by farmers signifies a shift towards more data-driven and efficient agricultural practices, aiming to meet the increasing global food demand sustainably.
Other critical end-user segments include Agriculture Technology Companies, Agriculture Consultants, Government Agencies, and Research Institutions. Agriculture Technology Companies play a pivotal role in developing and providing AI solutions tailored to agricultural needs, driving innovation in the sector. Agriculture Consultants use AI to offer more informed advice and strategies to their clients, enhancing the overall effectiveness of agricultural operations.
Government Agencies incorporate AI in policy-making and regulatory frameworks to support sustainable agricultural practices and food security. Research Institutions contribute to the advancement of AI in agriculture through cutting-edge research, pushing the boundaries of what's possible in agricultural science and technology.
Key Market Segments
Based on Crop Type
- Wheat
- Rice
- Corn
- Vegetables
- Other Crop Types
Based on Application
- Precision Farming
- Livestock Management
- Crop Management
- Soil Analysis
- Other Applications
Based on Technology
- Deep Learning
- Computer Vision
- Machine Learning
- Natural Language Processing
- Robotics
Based on End-User Industry
- Farmer
- Agriculture Technology Companies
- Agriculture Consultants
- Government Agencies
- Research Institutions
Growth Opportunities
Precision Farming Integration Offers Growth Opportunity
The integration of Generative AI with precision farming practices presents significant growth opportunities within the agricultural sector. By harnessing the power of AI to analyze vast amounts of data collected from sensors, satellites, and drones, farmers can make informed decisions that optimize the use of water, fertilizers, and pesticides.
This leads to higher crop yields and more sustainable farming practices. John Deere's See & Spray technology exemplifies this trend by using computer vision and AI to target herbicide application precisely, thereby reducing chemical usage and promoting healthier crops. Such innovations not only improve efficiency and productivity but also contribute to environmental sustainability, marking a major step forward in the evolution of farming practices.
Crop Yield Prediction Enhances Market Potential
Generative AI significantly boosts the agriculture market's potential through accurate crop yield predictions. These AI-driven forecasts enable farmers to plan more effectively, managing resources and schedules to optimize production.
By analyzing patterns in historical data, weather conditions, and soil quality, AI models offer predictions with impressive accuracy. This capability helps in better inventory management and contract negotiations, providing a solid foundation for operational and financial planning. The adoption of such technologies underscores a shift towards more data-centric and predictive approaches in agriculture, promising higher efficiency and profitability.
Automated Pest and Disease Detection Expands Market Reach
Automated pest and disease detection through Generative AI marks a transformative growth opportunity for the agriculture sector. Utilizing advanced image analysis, AI algorithms can quickly identify pest infestations or disease outbreaks by examining images captured by drones or smartphones. Early detection allows for swift interventions, significantly reducing potential crop damage and loss.
Companies like Taranis leverage deep learning to analyze crop imagery, detecting signs of stress before they escalate into larger issues. This not only enhances crop productivity but also reduces reliance on broad-spectrum chemical treatments, favoring more targeted and eco-friendly approaches. The adoption of these technologies expands the market's reach by offering scalable solutions that maintain crop health and yield.
Trending Factors
Rise of Smart Agriculture Initiatives Are Trending Factors
Smart agriculture initiatives are gaining momentum globally, significantly influencing the trend towards generative AI in agriculture. With the challenges of climate change, population growth, and limited resources pressing on the agricultural sector, governments, NGOs, and the private sector are increasingly turning to advanced technology solutions.
Generative AI stands out as a scalable and cost-effective option for enhancing productivity, sustainability, and resilience in farming. Its ability to provide actionable insights and automate complex decisions positions it as a central technology in the push towards smarter, more sustainable agricultural practices.
Integration of Internet of Things (IoT) Devices Are Trending Factors
The integration of Internet of Things (IoT) devices with generative AI systems is a prominent trend in the agricultural sector. Sensors, drones, and autonomous vehicles collect a wealth of real-time data on various environmental and crop conditions.
When this data is processed through generative AI algorithms, it enables precise, data-driven farming decisions. This technological synergy is revolutionizing agriculture by improving efficiency, reducing reliance on manual labor, and enhancing overall decision-making processes. As a result, the adoption of IoT and generative AI technologies is becoming increasingly prevalent, driving significant advancements in agricultural practices.
Regional Analysis
North America Dominates with 47.6% Market Share
North America's leading position in the Generative AI in Agriculture Market, with a 47.6% share, is propelled by several key factors. High levels of technological adoption, significant investments in research and development, and supportive government policies contribute to this dominance. The region's emphasis on innovation and sustainability in farming practices further fuels the integration of generative AI technologies.
The dynamics of North America's market are shaped by its advanced agricultural infrastructure, a strong ecosystem of tech companies, and a proactive approach to addressing agricultural challenges through technology. The presence of leading AI research institutions and tech giants facilitates the development and deployment of cutting-edge AI solutions in agriculture.
North America's influence in the Generative AI in Agriculture Market is expected to remain strong. Continuous investments in AI and the growing adoption of smart farming techniques are likely to further cement the region's leadership position. Moreover, the ongoing push for sustainable and efficient food production systems will drive innovation in generative AI applications.
Regional Market Shares:
- Europe: - Europe's market share is bolstered by its strong focus on sustainability and precision farming, supported by favorable regulations and initiatives.
- Asia Pacific: - The Asia Pacific region is experiencing rapid growth due to increasing technological adoption, particularly in countries like China and India, aimed at enhancing agricultural productivity.
- Middle East & Africa: While still developing, this region's market share is gradually increasing with the adoption of modern farming techniques to address food security and desertification challenges.
- Latin America: - Latin America's market share is growing, driven by the adoption of advanced agricultural technologies to improve crop yields and combat climatic challenges.
Key Regions and Countries
- North America
- The US
- Canada
- Mexico
- Western Europe
- Germany
- France
- The UK
- Spain
- Italy
- Portugal
- Ireland
- Austria
- Switzerland
- Benelux
- Nordic
- Rest of Western Europe
- Eastern Europe
- Russia
- Poland
- The Czech Republic
- Greece
- Rest of Eastern Europe
- APAC
- China
- Japan
- South Korea
- India
- Australia & New Zealand
- Indonesia
- Malaysia
- Philippines
- Singapore
- Thailand
- Vietnam
- Rest of APAC
- Latin America
- Brazil
- Colombia
- Chile
- Argentina
- Costa Rica
- Rest of Latin America
- Middle East & Africa
- Algeria
- Egypt
- Israel
- Kuwait
- Nigeria
- Saudi Arabia
- South Africa
- Turkey
- United Arab Emirates
- Rest of MEA
Key Players Analysis
In the Generative AI in Agriculture market, key players such as IBM Corp., Microsoft Corp., John Deere, The Climate Corporation, Ag Leader Technology, Trimble Inc., Prospera Technologies, Descartes Labs, Taranis, and Granular have made significant strides. Their contributions are pivotal in transforming agricultural practices through AI-driven insights, enhancing crop yield predictions, pest management, and climate adaptability.
IBM and Microsoft lead in providing foundational AI technologies and cloud services, supporting data-driven decision-making. John Deere and Trimble Inc. focus on precision agriculture, integrating AI into farm equipment and management systems to optimize operations. The Climate Corporation and Granular specialize in data analytics for climate and crop health monitoring, respectively, driving forward sustainability and efficiency.
Prospera Technologies and Taranis leverage AI for detailed field and crop monitoring, enabling precise interventions. Descartes Labs stands out for its geospatial analysis, offering unique perspectives on agricultural resources. Collectively, these key players and others in the sector are advancing the adoption of AI in agriculture, aiming for higher efficiency, sustainability, and food security, indicating a market rich in innovation and growth potential.
Market Key Players
- IBM Corp.
- Microsoft Corp.
- John Deere
- The Climate Corporation (a subsidiary of Bayer)
- Ag Leader Technology
- Trimble Inc.
- Prospera Technologies
- Descartes Labs
- Taranis
- Granular (a Corteva Agriscience company)
- Other Key Players
Recent Development
- April 2023 - With a brand new tool that makes use of an algorithm that generates AI to create new product concepts based upon insights from its platforms for spotting trends, Singapore-based Ai Palette is expanding its capabilities to help food and beverage companies speed up the process of developing for the creation of new products. In addition, it has completed the "missing part" between Ai Palette's latest concept screening instrument (Screen Winner) as well as its analytics platform that is powered by AI (Foresight Engine), the new concept generator for products is referred to as "Concept Genie," could dramatically speed up the development process.
- November 2022 - For a broad variety of applications within the fields of precision agriculture and environmental monitoring, DJI Agriculture introduces the Mavic 3 Multispectral model, equipped with an imaging system that rapidly captures the growth of crops to ensure higher yields in crop production. This device will aid farmers from all over the world in enhancing the efficiency and quality of their crops while also reducing costs and increasing the amount of income.
Report Scope:
Report Features Description Market Value (2022) USD 125 Mn Forecast Revenue (2032) USD 1083.9 Mn CAGR (2023-2032) 24.8% Base Year for Estimation 2022 Historic Period 2016-2022 Forecast Period 2023-2032 Report Coverage Revenue Forecast, Market Dynamics, COVID-19 Impact, Competitive Landscape, Recent Developments Segments Covered Based on Crop Type (Wheat, Rice, Corn, Vegetables, Other Crop Types)
Based on Application (Precision Farming, Livestock Management, Crop Management, Soil Analysis, Other Applications)
Based on Technology (Deep Learning, Computer Vision, Machine Learning, Natural Language Processing, Robotics)
Based on End-User Industry (Farmers, Agriculture Technology Companies, Agriculture Consultants, Government Agencies, Research Institutions)Regional Analysis North America – The US, Canada, & Mexico; Western Europe – Germany, France, The UK, Spain, Italy, Portugal, Ireland, Austria, Switzerland, Benelux, Nordic, & Rest of Western Europe; Eastern Europe – Russia, Poland, The Czech Republic, Greece, & Rest of Eastern Europe; APAC – China, Japan, South Korea, India, Australia & New Zealand, Indonesia, Malaysia, Philippines, Singapore, Thailand, Vietnam, & Rest of APAC; Latin America – Brazil, Colombia, Chile, Argentina, Costa Rica, & Rest of Latin America; Middle East & Africa – Algeria, Egypt, Israel, Kuwait, Nigeria, Saudi Arabia, South Africa, Turkey, United Arab Emirates, & Rest of MEA Competitive Landscape IBM Corp., Microsoft Corp., John Deere, The Climate Corporation (a subsidiary of Bayer), Ag Leader Technology, Trimble Inc., Prospera Technologies, Descartes Labs, Taranis, Granular (a Corteva Agriscience company), Other Key Players Customization Scope Customization for segments, region/country-level will be provided. Moreover, additional customization can be done based on the requirements. Purchase Options We have three licenses to opt for: Single User License, Multi-User License (Up to 5 Users), Corporate Use License (Unlimited User and Printable PDF) -
- 1. Executive Summary
- 1.1. Definition
- 1.2. Taxonomy
- 1.3. Research Scope
- 1.4. Key Analysis
- 1.5. Key Findings by Major Segments
- 1.6. Top strategies by Major Players
- 2. Global Generative AI in Agriculture Market Overview
- 2.1. Generative AI in Agriculture Market Dynamics
- 2.1.1. Drivers
- 2.1.2. Opportunities
- 2.1.3. Restraints
- 2.1.4. Challenges
- 2.2. Macro-economic Factors
- 2.3. Regulatory Framework
- 2.4. Market Investment Feasibility Index
- 2.5. PEST Analysis
- 2.6. PORTER’S Five Force Analysis
- 2.7. Drivers & Restraints Impact Analysis
- 2.8. Industry Chain Analysis
- 2.9. Cost Structure Analysis
- 2.10. Marketing Strategy
- 2.11. Russia-Ukraine War Impact Analysis
- 2.12. Opportunity Map Analysis
- 2.13. Market Competition Scenario Analysis
- 2.14. Product Life Cycle Analysis
- 2.15. Opportunity Orbits
- 2.16. Manufacturer Intensity Map
- 2.17. Major Companies sales by Value & Volume
- 2.1. Generative AI in Agriculture Market Dynamics
- 3. Global Generative AI in Agriculture Market Analysis, Opportunity and Forecast, 2016-2032
- 3.1. Global Generative AI in Agriculture Market Analysis, 2016-2021
- 3.2. Global Generative AI in Agriculture Market Opportunity and Forecast, 2023-2032
- 3.3. Global Generative AI in Agriculture Market Analysis, Opportunity and Forecast, By Crop Type, 2016-2032
- 3.3.1. Global Generative AI in Agriculture Market Analysis by Crop Type: Introduction
- 3.3.2. Market Size Absolute $ Opportunity Analysis and Forecast, By Crop Type, 2016-2032
- 3.3.3. Wheat
- 3.3.4. Rice
- 3.3.5. Corn
- 3.3.6. Vegetables
- 3.3.7. Other Crop Types
- 3.4. Global Generative AI in Agriculture Market Analysis, Opportunity and Forecast, By Application, 2016-2032
- 3.4.1. Global Generative AI in Agriculture Market Analysis by Application: Introduction
- 3.4.2. Market Size Absolute $ Opportunity Analysis and Forecast, By Application, 2016-2032
- 3.4.3. Precision Farming
- 3.4.4. Livestock Management
- 3.4.5. Crop Management
- 3.4.6. Soil Analysis
- 3.4.7. Other Applications
- 3.5. Global Generative AI in Agriculture Market Analysis, Opportunity and Forecast, By Technology, 2016-2032
- 3.5.1. Global Generative AI in Agriculture Market Analysis by Technology: Introduction
- 3.5.2. Market Size Absolute $ Opportunity Analysis and Forecast, By Technology, 2016-2032
- 3.5.3. Deep Learning
- 3.5.4. Computer Vision
- 3.5.5. Machine Learning
- 3.5.6. Natural Language Processing
- 3.5.7. Robotics
- 3.6. Global Generative AI in Agriculture Market Analysis, Opportunity and Forecast, By End-User, 2016-2032
- 3.6.1. Global Generative AI in Agriculture Market Analysis by End-User: Introduction
- 3.6.2. Market Size Absolute $ Opportunity Analysis and Forecast, By End-User, 2016-2032
- 3.6.3. Farmers
- 3.6.4. Agriculture Technology Companies
- 3.6.5. Agriculture Consultants
- 3.6.6. Government Agencies
- 3.6.7. Research Institutions
- 4. North America Generative AI in Agriculture Market Analysis, Opportunity and Forecast, 2016-2032
- 4.1. North America Generative AI in Agriculture Market Analysis, 2016-2021
- 4.2. North America Generative AI in Agriculture Market Opportunity and Forecast, 2023-2032
- 4.3. North America Generative AI in Agriculture Market Analysis, Opportunity and Forecast, By Crop Type, 2016-2032
- 4.3.1. North America Generative AI in Agriculture Market Analysis by Crop Type: Introduction
- 4.3.2. Market Size Absolute $ Opportunity Analysis and Forecast, By Crop Type, 2016-2032
- 4.3.3. Wheat
- 4.3.4. Rice
- 4.3.5. Corn
- 4.3.6. Vegetables
- 4.3.7. Other Crop Types
- 4.4. North America Generative AI in Agriculture Market Analysis, Opportunity and Forecast, By Application, 2016-2032
- 4.4.1. North America Generative AI in Agriculture Market Analysis by Application: Introduction
- 4.4.2. Market Size Absolute $ Opportunity Analysis and Forecast, By Application, 2016-2032
- 4.4.3. Precision Farming
- 4.4.4. Livestock Management
- 4.4.5. Crop Management
- 4.4.6. Soil Analysis
- 4.4.7. Other Applications
- 4.5. North America Generative AI in Agriculture Market Analysis, Opportunity and Forecast, By Technology, 2016-2032
- 4.5.1. North America Generative AI in Agriculture Market Analysis by Technology: Introduction
- 4.5.2. Market Size Absolute $ Opportunity Analysis and Forecast, By Technology, 2016-2032
- 4.5.3. Deep Learning
- 4.5.4. Computer Vision
- 4.5.5. Machine Learning
- 4.5.6. Natural Language Processing
- 4.5.7. Robotics
- 4.6. North America Generative AI in Agriculture Market Analysis, Opportunity and Forecast, By End-User, 2016-2032
- 4.6.1. North America Generative AI in Agriculture Market Analysis by End-User: Introduction
- 4.6.2. Market Size Absolute $ Opportunity Analysis and Forecast, By End-User, 2016-2032
- 4.6.3. Farmers
- 4.6.4. Agriculture Technology Companies
- 4.6.5. Agriculture Consultants
- 4.6.6. Government Agencies
- 4.6.7. Research Institutions
- 4.7. North America Generative AI in Agriculture Market Analysis, Opportunity and Forecast, By Country , 2016-2032
- 4.7.1. North America Generative AI in Agriculture Market Analysis by Country : Introduction
- 4.7.2. Market Size Absolute $ Opportunity Analysis and Forecast, Country , 2016-2032
- 4.7.2.1. The US
- 4.7.2.2. Canada
- 4.7.2.3. Mexico
- 5. Western Europe Generative AI in Agriculture Market Analysis, Opportunity and Forecast, 2016-2032
- 5.1. Western Europe Generative AI in Agriculture Market Analysis, 2016-2021
- 5.2. Western Europe Generative AI in Agriculture Market Opportunity and Forecast, 2023-2032
- 5.3. Western Europe Generative AI in Agriculture Market Analysis, Opportunity and Forecast, By Crop Type, 2016-2032
- 5.3.1. Western Europe Generative AI in Agriculture Market Analysis by Crop Type: Introduction
- 5.3.2. Market Size Absolute $ Opportunity Analysis and Forecast, By Crop Type, 2016-2032
- 5.3.3. Wheat
- 5.3.4. Rice
- 5.3.5. Corn
- 5.3.6. Vegetables
- 5.3.7. Other Crop Types
- 5.4. Western Europe Generative AI in Agriculture Market Analysis, Opportunity and Forecast, By Application, 2016-2032
- 5.4.1. Western Europe Generative AI in Agriculture Market Analysis by Application: Introduction
- 5.4.2. Market Size Absolute $ Opportunity Analysis and Forecast, By Application, 2016-2032
- 5.4.3. Precision Farming
- 5.4.4. Livestock Management
- 5.4.5. Crop Management
- 5.4.6. Soil Analysis
- 5.4.7. Other Applications
- 5.5. Western Europe Generative AI in Agriculture Market Analysis, Opportunity and Forecast, By Technology, 2016-2032
- 5.5.1. Western Europe Generative AI in Agriculture Market Analysis by Technology: Introduction
- 5.5.2. Market Size Absolute $ Opportunity Analysis and Forecast, By Technology, 2016-2032
- 5.5.3. Deep Learning
- 5.5.4. Computer Vision
- 5.5.5. Machine Learning
- 5.5.6. Natural Language Processing
- 5.5.7. Robotics
- 5.6. Western Europe Generative AI in Agriculture Market Analysis, Opportunity and Forecast, By End-User, 2016-2032
- 5.6.1. Western Europe Generative AI in Agriculture Market Analysis by End-User: Introduction
- 5.6.2. Market Size Absolute $ Opportunity Analysis and Forecast, By End-User, 2016-2032
- 5.6.3. Farmers
- 5.6.4. Agriculture Technology Companies
- 5.6.5. Agriculture Consultants
- 5.6.6. Government Agencies
- 5.6.7. Research Institutions
- 5.7. Western Europe Generative AI in Agriculture Market Analysis, Opportunity and Forecast, By Country , 2016-2032
- 5.7.1. Western Europe Generative AI in Agriculture Market Analysis by Country : Introduction
- 5.7.2. Market Size Absolute $ Opportunity Analysis and Forecast, Country , 2016-2032
- 5.7.2.1. Germany
- 5.7.2.2. France
- 5.7.2.3. The UK
- 5.7.2.4. Spain
- 5.7.2.5. Italy
- 5.7.2.6. Portugal
- 5.7.2.7. Ireland
- 5.7.2.8. Austria
- 5.7.2.9. Switzerland
- 5.7.2.10. Benelux
- 5.7.2.11. Nordic
- 5.7.2.12. Rest of Western Europe
- 6. Eastern Europe Generative AI in Agriculture Market Analysis, Opportunity and Forecast, 2016-2032
- 6.1. Eastern Europe Generative AI in Agriculture Market Analysis, 2016-2021
- 6.2. Eastern Europe Generative AI in Agriculture Market Opportunity and Forecast, 2023-2032
- 6.3. Eastern Europe Generative AI in Agriculture Market Analysis, Opportunity and Forecast, By Crop Type, 2016-2032
- 6.3.1. Eastern Europe Generative AI in Agriculture Market Analysis by Crop Type: Introduction
- 6.3.2. Market Size Absolute $ Opportunity Analysis and Forecast, By Crop Type, 2016-2032
- 6.3.3. Wheat
- 6.3.4. Rice
- 6.3.5. Corn
- 6.3.6. Vegetables
- 6.3.7. Other Crop Types
- 6.4. Eastern Europe Generative AI in Agriculture Market Analysis, Opportunity and Forecast, By Application, 2016-2032
- 6.4.1. Eastern Europe Generative AI in Agriculture Market Analysis by Application: Introduction
- 6.4.2. Market Size Absolute $ Opportunity Analysis and Forecast, By Application, 2016-2032
- 6.4.3. Precision Farming
- 6.4.4. Livestock Management
- 6.4.5. Crop Management
- 6.4.6. Soil Analysis
- 6.4.7. Other Applications
- 6.5. Eastern Europe Generative AI in Agriculture Market Analysis, Opportunity and Forecast, By Technology, 2016-2032
- 6.5.1. Eastern Europe Generative AI in Agriculture Market Analysis by Technology: Introduction
- 6.5.2. Market Size Absolute $ Opportunity Analysis and Forecast, By Technology, 2016-2032
- 6.5.3. Deep Learning
- 6.5.4. Computer Vision
- 6.5.5. Machine Learning
- 6.5.6. Natural Language Processing
- 6.5.7. Robotics
- 6.6. Eastern Europe Generative AI in Agriculture Market Analysis, Opportunity and Forecast, By End-User, 2016-2032
- 6.6.1. Eastern Europe Generative AI in Agriculture Market Analysis by End-User: Introduction
- 6.6.2. Market Size Absolute $ Opportunity Analysis and Forecast, By End-User, 2016-2032
- 6.6.3. Farmers
- 6.6.4. Agriculture Technology Companies
- 6.6.5. Agriculture Consultants
- 6.6.6. Government Agencies
- 6.6.7. Research Institutions
- 6.7. Eastern Europe Generative AI in Agriculture Market Analysis, Opportunity and Forecast, By Country , 2016-2032
- 6.7.1. Eastern Europe Generative AI in Agriculture Market Analysis by Country : Introduction
- 6.7.2. Market Size Absolute $ Opportunity Analysis and Forecast, Country , 2016-2032
- 6.7.2.1. Russia
- 6.7.2.2. Poland
- 6.7.2.3. The Czech Republic
- 6.7.2.4. Greece
- 6.7.2.5. Rest of Eastern Europe
- 7. APAC Generative AI in Agriculture Market Analysis, Opportunity and Forecast, 2016-2032
- 7.1. APAC Generative AI in Agriculture Market Analysis, 2016-2021
- 7.2. APAC Generative AI in Agriculture Market Opportunity and Forecast, 2023-2032
- 7.3. APAC Generative AI in Agriculture Market Analysis, Opportunity and Forecast, By Crop Type, 2016-2032
- 7.3.1. APAC Generative AI in Agriculture Market Analysis by Crop Type: Introduction
- 7.3.2. Market Size Absolute $ Opportunity Analysis and Forecast, By Crop Type, 2016-2032
- 7.3.3. Wheat
- 7.3.4. Rice
- 7.3.5. Corn
- 7.3.6. Vegetables
- 7.3.7. Other Crop Types
- 7.4. APAC Generative AI in Agriculture Market Analysis, Opportunity and Forecast, By Application, 2016-2032
- 7.4.1. APAC Generative AI in Agriculture Market Analysis by Application: Introduction
- 7.4.2. Market Size Absolute $ Opportunity Analysis and Forecast, By Application, 2016-2032
- 7.4.3. Precision Farming
- 7.4.4. Livestock Management
- 7.4.5. Crop Management
- 7.4.6. Soil Analysis
- 7.4.7. Other Applications
- 7.5. APAC Generative AI in Agriculture Market Analysis, Opportunity and Forecast, By Technology, 2016-2032
- 7.5.1. APAC Generative AI in Agriculture Market Analysis by Technology: Introduction
- 7.5.2. Market Size Absolute $ Opportunity Analysis and Forecast, By Technology, 2016-2032
- 7.5.3. Deep Learning
- 7.5.4. Computer Vision
- 7.5.5. Machine Learning
- 7.5.6. Natural Language Processing
- 7.5.7. Robotics
- 7.6. APAC Generative AI in Agriculture Market Analysis, Opportunity and Forecast, By End-User, 2016-2032
- 7.6.1. APAC Generative AI in Agriculture Market Analysis by End-User: Introduction
- 7.6.2. Market Size Absolute $ Opportunity Analysis and Forecast, By End-User, 2016-2032
- 7.6.3. Farmers
- 7.6.4. Agriculture Technology Companies
- 7.6.5. Agriculture Consultants
- 7.6.6. Government Agencies
- 7.6.7. Research Institutions
- 7.7. APAC Generative AI in Agriculture Market Analysis, Opportunity and Forecast, By Country , 2016-2032
- 7.7.1. APAC Generative AI in Agriculture Market Analysis by Country : Introduction
- 7.7.2. Market Size Absolute $ Opportunity Analysis and Forecast, Country , 2016-2032
- 7.7.2.1. China
- 7.7.2.2. Japan
- 7.7.2.3. South Korea
- 7.7.2.4. India
- 7.7.2.5. Australia & New Zeland
- 7.7.2.6. Indonesia
- 7.7.2.7. Malaysia
- 7.7.2.8. Philippines
- 7.7.2.9. Singapore
- 7.7.2.10. Thailand
- 7.7.2.11. Vietnam
- 7.7.2.12. Rest of APAC
- 8. Latin America Generative AI in Agriculture Market Analysis, Opportunity and Forecast, 2016-2032
- 8.1. Latin America Generative AI in Agriculture Market Analysis, 2016-2021
- 8.2. Latin America Generative AI in Agriculture Market Opportunity and Forecast, 2023-2032
- 8.3. Latin America Generative AI in Agriculture Market Analysis, Opportunity and Forecast, By Crop Type, 2016-2032
- 8.3.1. Latin America Generative AI in Agriculture Market Analysis by Crop Type: Introduction
- 8.3.2. Market Size Absolute $ Opportunity Analysis and Forecast, By Crop Type, 2016-2032
- 8.3.3. Wheat
- 8.3.4. Rice
- 8.3.5. Corn
- 8.3.6. Vegetables
- 8.3.7. Other Crop Types
- 8.4. Latin America Generative AI in Agriculture Market Analysis, Opportunity and Forecast, By Application, 2016-2032
- 8.4.1. Latin America Generative AI in Agriculture Market Analysis by Application: Introduction
- 8.4.2. Market Size Absolute $ Opportunity Analysis and Forecast, By Application, 2016-2032
- 8.4.3. Precision Farming
- 8.4.4. Livestock Management
- 8.4.5. Crop Management
- 8.4.6. Soil Analysis
- 8.4.7. Other Applications
- 8.5. Latin America Generative AI in Agriculture Market Analysis, Opportunity and Forecast, By Technology, 2016-2032
- 8.5.1. Latin America Generative AI in Agriculture Market Analysis by Technology: Introduction
- 8.5.2. Market Size Absolute $ Opportunity Analysis and Forecast, By Technology, 2016-2032
- 8.5.3. Deep Learning
- 8.5.4. Computer Vision
- 8.5.5. Machine Learning
- 8.5.6. Natural Language Processing
- 8.5.7. Robotics
- 8.6. Latin America Generative AI in Agriculture Market Analysis, Opportunity and Forecast, By End-User, 2016-2032
- 8.6.1. Latin America Generative AI in Agriculture Market Analysis by End-User: Introduction
- 8.6.2. Market Size Absolute $ Opportunity Analysis and Forecast, By End-User, 2016-2032
- 8.6.3. Farmers
- 8.6.4. Agriculture Technology Companies
- 8.6.5. Agriculture Consultants
- 8.6.6. Government Agencies
- 8.6.7. Research Institutions
- 8.7. Latin America Generative AI in Agriculture Market Analysis, Opportunity and Forecast, By Country , 2016-2032
- 8.7.1. Latin America Generative AI in Agriculture Market Analysis by Country : Introduction
- 8.7.2. Market Size Absolute $ Opportunity Analysis and Forecast, Country , 2016-2032
- 8.7.2.1. Brazil
- 8.7.2.2. Colombia
- 8.7.2.3. Chile
- 8.7.2.4. Argentina
- 8.7.2.5. Costa Rica
- 8.7.2.6. Rest of Latin America
- 9. Middle East & Africa Generative AI in Agriculture Market Analysis, Opportunity and Forecast, 2016-2032
- 9.1. Middle East & Africa Generative AI in Agriculture Market Analysis, 2016-2021
- 9.2. Middle East & Africa Generative AI in Agriculture Market Opportunity and Forecast, 2023-2032
- 9.3. Middle East & Africa Generative AI in Agriculture Market Analysis, Opportunity and Forecast, By Crop Type, 2016-2032
- 9.3.1. Middle East & Africa Generative AI in Agriculture Market Analysis by Crop Type: Introduction
- 9.3.2. Market Size Absolute $ Opportunity Analysis and Forecast, By Crop Type, 2016-2032
- 9.3.3. Wheat
- 9.3.4. Rice
- 9.3.5. Corn
- 9.3.6. Vegetables
- 9.3.7. Other Crop Types
- 9.4. Middle East & Africa Generative AI in Agriculture Market Analysis, Opportunity and Forecast, By Application, 2016-2032
- 9.4.1. Middle East & Africa Generative AI in Agriculture Market Analysis by Application: Introduction
- 9.4.2. Market Size Absolute $ Opportunity Analysis and Forecast, By Application, 2016-2032
- 9.4.3. Precision Farming
- 9.4.4. Livestock Management
- 9.4.5. Crop Management
- 9.4.6. Soil Analysis
- 9.4.7. Other Applications
- 9.5. Middle East & Africa Generative AI in Agriculture Market Analysis, Opportunity and Forecast, By Technology, 2016-2032
- 9.5.1. Middle East & Africa Generative AI in Agriculture Market Analysis by Technology: Introduction
- 9.5.2. Market Size Absolute $ Opportunity Analysis and Forecast, By Technology, 2016-2032
- 9.5.3. Deep Learning
- 9.5.4. Computer Vision
- 9.5.5. Machine Learning
- 9.5.6. Natural Language Processing
- 9.5.7. Robotics
- 9.6. Middle East & Africa Generative AI in Agriculture Market Analysis, Opportunity and Forecast, By End-User, 2016-2032
- 9.6.1. Middle East & Africa Generative AI in Agriculture Market Analysis by End-User: Introduction
- 9.6.2. Market Size Absolute $ Opportunity Analysis and Forecast, By End-User, 2016-2032
- 9.6.3. Farmers
- 9.6.4. Agriculture Technology Companies
- 9.6.5. Agriculture Consultants
- 9.6.6. Government Agencies
- 9.6.7. Research Institutions
- 9.7. Middle East & Africa Generative AI in Agriculture Market Analysis, Opportunity and Forecast, By Country , 2016-2032
- 9.7.1. Middle East & Africa Generative AI in Agriculture Market Analysis by Country : Introduction
- 9.7.2. Market Size Absolute $ Opportunity Analysis and Forecast, Country , 2016-2032
- 9.7.2.1. Algeria
- 9.7.2.2. Egypt
- 9.7.2.3. Israel
- 9.7.2.4. Kuwait
- 9.7.2.5. Nigeria
- 9.7.2.6. Saudi Arabia
- 9.7.2.7. South Africa
- 9.7.2.8. Turkey
- 9.7.2.9. The UAE
- 9.7.2.10. Rest of MEA
- 10. Global Generative AI in Agriculture Market Analysis, Opportunity and Forecast, By Region , 2016-2032
- 10.1. Global Generative AI in Agriculture Market Analysis by Region : Introduction
- 10.2. Market Size Absolute $ Opportunity Analysis and Forecast, By Region , 2016-2032
- 10.2.1. North America
- 10.2.2. Western Europe
- 10.2.3. Eastern Europe
- 10.2.4. APAC
- 10.2.5. Latin America
- 10.2.6. Middle East & Africa
- 11. Global Generative AI in Agriculture Market Competitive Landscape, Market Share Analysis, and Company Profiles
- 11.1. Market Share Analysis
- 11.2. Company Profiles
- 11.3. IBM Corp.
- 11.3.1. Company Overview
- 11.3.2. Financial Highlights
- 11.3.3. Product Portfolio
- 11.3.4. SWOT Analysis
- 11.3.5. Key Strategies and Developments
- 11.4. Microsoft Corp.
- 11.4.1. Company Overview
- 11.4.2. Financial Highlights
- 11.4.3. Product Portfolio
- 11.4.4. SWOT Analysis
- 11.4.5. Key Strategies and Developments
- 11.5. John Deere
- 11.5.1. Company Overview
- 11.5.2. Financial Highlights
- 11.5.3. Product Portfolio
- 11.5.4. SWOT Analysis
- 11.5.5. Key Strategies and Developments
- 11.6. The Climate Corporation (a subsidiary of Bayer)
- 11.6.1. Company Overview
- 11.6.2. Financial Highlights
- 11.6.3. Product Portfolio
- 11.6.4. SWOT Analysis
- 11.6.5. Key Strategies and Developments
- 11.7. Ag Leader Technology
- 11.7.1. Company Overview
- 11.7.2. Financial Highlights
- 11.7.3. Product Portfolio
- 11.7.4. SWOT Analysis
- 11.7.5. Key Strategies and Developments
- 11.9. Prospera Technologies
- 11.9.1. Company Overview
- 11.9.2. Financial Highlights
- 11.9.3. Product Portfolio
- 11.9.4. SWOT Analysis
- 11.9.5. Key Strategies and Developments
- 11.10. Descartes Labs
- 11.10.1. Company Overview
- 11.10.2. Financial Highlights
- 11.10.3. Product Portfolio
- 11.10.4. SWOT Analysis
- 11.10.5. Key Strategies and Developments
- 11.11. Taranis
- 11.11.1. Company Overview
- 11.11.2. Financial Highlights
- 11.11.3. Product Portfolio
- 11.11.4. SWOT Analysis
- 11.11.5. Key Strategies and Developments
- 11.12. Granular (a Corteva Agriscience company)
- 11.12.1. Company Overview
- 11.12.2. Financial Highlights
- 11.12.3. Product Portfolio
- 11.12.4. SWOT Analysis
- 11.12.5. Key Strategies and Developments
- 11.13. Other Key Players
- 11.13.1. Company Overview
- 11.13.2. Financial Highlights
- 11.13.3. Product Portfolio
- 11.13.4. SWOT Analysis
- 11.13.5. Key Strategies and Developments
- 12. Assumptions and Acronyms
- 13. Research Methodology
- 14. Contact
- List of Figures
- Figure 1: Global Generative AI in Agriculture Market Revenue (US$ Mn) Market Share by Crop Type in 2022
- Figure 2: Global Generative AI in Agriculture Market Attractiveness Analysis by Crop Type, 2016-2032
- Figure 3: Global Generative AI in Agriculture Market Revenue (US$ Mn) Market Share by Applicationin 2022
- Figure 4: Global Generative AI in Agriculture Market Attractiveness Analysis by Application, 2016-2032
- Figure 5: Global Generative AI in Agriculture Market Revenue (US$ Mn) Market Share by Technologyin 2022
- Figure 6: Global Generative AI in Agriculture Market Attractiveness Analysis by Technology, 2016-2032
- Figure 7: Global Generative AI in Agriculture Market Revenue (US$ Mn) Market Share by End-Userin 2022
- Figure 8: Global Generative AI in Agriculture Market Attractiveness Analysis by End-User, 2016-2032
- Figure 9: Global Generative AI in Agriculture Market Revenue (US$ Mn) Market Share by Region in 2022
- Figure 10: Global Generative AI in Agriculture Market Attractiveness Analysis by Region, 2016-2032
- Figure 11: Global Generative AI in Agriculture Market Revenue (US$ Mn) (2016-2032)
- Figure 12: Global Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Region (2016-2032)
- Figure 13: Global Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Crop Type (2016-2032)
- Figure 14: Global Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Application (2016-2032)
- Figure 15: Global Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Technology (2016-2032)
- Figure 16: Global Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by End-User (2016-2032)
- Figure 17: Global Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Region (2016-2032)
- Figure 18: Global Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Crop Type (2016-2032)
- Figure 19: Global Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Application (2016-2032)
- Figure 20: Global Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Technology (2016-2032)
- Figure 21: Global Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by End-User (2016-2032)
- Figure 22: Global Generative AI in Agriculture Market Share Comparison by Region (2016-2032)
- Figure 23: Global Generative AI in Agriculture Market Share Comparison by Crop Type (2016-2032)
- Figure 24: Global Generative AI in Agriculture Market Share Comparison by Application (2016-2032)
- Figure 25: Global Generative AI in Agriculture Market Share Comparison by Technology (2016-2032)
- Figure 26: Global Generative AI in Agriculture Market Share Comparison by End-User (2016-2032)
- Figure 27: North America Generative AI in Agriculture Market Revenue (US$ Mn) Market Share by Crop Typein 2022
- Figure 28: North America Generative AI in Agriculture Market Attractiveness Analysis by Crop Type, 2016-2032
- Figure 29: North America Generative AI in Agriculture Market Revenue (US$ Mn) Market Share by Applicationin 2022
- Figure 30: North America Generative AI in Agriculture Market Attractiveness Analysis by Application, 2016-2032
- Figure 31: North America Generative AI in Agriculture Market Revenue (US$ Mn) Market Share by Technologyin 2022
- Figure 32: North America Generative AI in Agriculture Market Attractiveness Analysis by Technology, 2016-2032
- Figure 33: North America Generative AI in Agriculture Market Revenue (US$ Mn) Market Share by End-Userin 2022
- Figure 34: North America Generative AI in Agriculture Market Attractiveness Analysis by End-User, 2016-2032
- Figure 35: North America Generative AI in Agriculture Market Revenue (US$ Mn) Market Share by Country in 2022
- Figure 36: North America Generative AI in Agriculture Market Attractiveness Analysis by Country, 2016-2032
- Figure 37: North America Generative AI in Agriculture Market Revenue (US$ Mn) (2016-2032)
- Figure 38: North America Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Country (2016-2032)
- Figure 39: North America Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Crop Type (2016-2032)
- Figure 40: North America Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Application (2016-2032)
- Figure 41: North America Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Technology (2016-2032)
- Figure 42: North America Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by End-User (2016-2032)
- Figure 43: North America Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Country (2016-2032)
- Figure 44: North America Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Crop Type (2016-2032)
- Figure 45: North America Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Application (2016-2032)
- Figure 46: North America Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Technology (2016-2032)
- Figure 47: North America Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by End-User (2016-2032)
- Figure 48: North America Generative AI in Agriculture Market Share Comparison by Country (2016-2032)
- Figure 49: North America Generative AI in Agriculture Market Share Comparison by Crop Type (2016-2032)
- Figure 50: North America Generative AI in Agriculture Market Share Comparison by Application (2016-2032)
- Figure 51: North America Generative AI in Agriculture Market Share Comparison by Technology (2016-2032)
- Figure 52: North America Generative AI in Agriculture Market Share Comparison by End-User (2016-2032)
- Figure 53: Western Europe Generative AI in Agriculture Market Revenue (US$ Mn) Market Share by Crop Typein 2022
- Figure 54: Western Europe Generative AI in Agriculture Market Attractiveness Analysis by Crop Type, 2016-2032
- Figure 55: Western Europe Generative AI in Agriculture Market Revenue (US$ Mn) Market Share by Applicationin 2022
- Figure 56: Western Europe Generative AI in Agriculture Market Attractiveness Analysis by Application, 2016-2032
- Figure 57: Western Europe Generative AI in Agriculture Market Revenue (US$ Mn) Market Share by Technologyin 2022
- Figure 58: Western Europe Generative AI in Agriculture Market Attractiveness Analysis by Technology, 2016-2032
- Figure 59: Western Europe Generative AI in Agriculture Market Revenue (US$ Mn) Market Share by End-Userin 2022
- Figure 60: Western Europe Generative AI in Agriculture Market Attractiveness Analysis by End-User, 2016-2032
- Figure 61: Western Europe Generative AI in Agriculture Market Revenue (US$ Mn) Market Share by Country in 2022
- Figure 62: Western Europe Generative AI in Agriculture Market Attractiveness Analysis by Country, 2016-2032
- Figure 63: Western Europe Generative AI in Agriculture Market Revenue (US$ Mn) (2016-2032)
- Figure 64: Western Europe Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Country (2016-2032)
- Figure 65: Western Europe Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Crop Type (2016-2032)
- Figure 66: Western Europe Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Application (2016-2032)
- Figure 67: Western Europe Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Technology (2016-2032)
- Figure 68: Western Europe Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by End-User (2016-2032)
- Figure 69: Western Europe Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Country (2016-2032)
- Figure 70: Western Europe Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Crop Type (2016-2032)
- Figure 71: Western Europe Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Application (2016-2032)
- Figure 72: Western Europe Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Technology (2016-2032)
- Figure 73: Western Europe Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by End-User (2016-2032)
- Figure 74: Western Europe Generative AI in Agriculture Market Share Comparison by Country (2016-2032)
- Figure 75: Western Europe Generative AI in Agriculture Market Share Comparison by Crop Type (2016-2032)
- Figure 76: Western Europe Generative AI in Agriculture Market Share Comparison by Application (2016-2032)
- Figure 77: Western Europe Generative AI in Agriculture Market Share Comparison by Technology (2016-2032)
- Figure 78: Western Europe Generative AI in Agriculture Market Share Comparison by End-User (2016-2032)
- Figure 79: Eastern Europe Generative AI in Agriculture Market Revenue (US$ Mn) Market Share by Crop Typein 2022
- Figure 80: Eastern Europe Generative AI in Agriculture Market Attractiveness Analysis by Crop Type, 2016-2032
- Figure 81: Eastern Europe Generative AI in Agriculture Market Revenue (US$ Mn) Market Share by Applicationin 2022
- Figure 82: Eastern Europe Generative AI in Agriculture Market Attractiveness Analysis by Application, 2016-2032
- Figure 83: Eastern Europe Generative AI in Agriculture Market Revenue (US$ Mn) Market Share by Technologyin 2022
- Figure 84: Eastern Europe Generative AI in Agriculture Market Attractiveness Analysis by Technology, 2016-2032
- Figure 85: Eastern Europe Generative AI in Agriculture Market Revenue (US$ Mn) Market Share by End-Userin 2022
- Figure 86: Eastern Europe Generative AI in Agriculture Market Attractiveness Analysis by End-User, 2016-2032
- Figure 87: Eastern Europe Generative AI in Agriculture Market Revenue (US$ Mn) Market Share by Country in 2022
- Figure 88: Eastern Europe Generative AI in Agriculture Market Attractiveness Analysis by Country, 2016-2032
- Figure 89: Eastern Europe Generative AI in Agriculture Market Revenue (US$ Mn) (2016-2032)
- Figure 90: Eastern Europe Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Country (2016-2032)
- Figure 91: Eastern Europe Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Crop Type (2016-2032)
- Figure 92: Eastern Europe Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Application (2016-2032)
- Figure 93: Eastern Europe Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Technology (2016-2032)
- Figure 94: Eastern Europe Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by End-User (2016-2032)
- Figure 95: Eastern Europe Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Country (2016-2032)
- Figure 96: Eastern Europe Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Crop Type (2016-2032)
- Figure 97: Eastern Europe Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Application (2016-2032)
- Figure 98: Eastern Europe Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Technology (2016-2032)
- Figure 99: Eastern Europe Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by End-User (2016-2032)
- Figure 100: Eastern Europe Generative AI in Agriculture Market Share Comparison by Country (2016-2032)
- Figure 101: Eastern Europe Generative AI in Agriculture Market Share Comparison by Crop Type (2016-2032)
- Figure 102: Eastern Europe Generative AI in Agriculture Market Share Comparison by Application (2016-2032)
- Figure 103: Eastern Europe Generative AI in Agriculture Market Share Comparison by Technology (2016-2032)
- Figure 104: Eastern Europe Generative AI in Agriculture Market Share Comparison by End-User (2016-2032)
- Figure 105: APAC Generative AI in Agriculture Market Revenue (US$ Mn) Market Share by Crop Typein 2022
- Figure 106: APAC Generative AI in Agriculture Market Attractiveness Analysis by Crop Type, 2016-2032
- Figure 107: APAC Generative AI in Agriculture Market Revenue (US$ Mn) Market Share by Applicationin 2022
- Figure 108: APAC Generative AI in Agriculture Market Attractiveness Analysis by Application, 2016-2032
- Figure 109: APAC Generative AI in Agriculture Market Revenue (US$ Mn) Market Share by Technologyin 2022
- Figure 110: APAC Generative AI in Agriculture Market Attractiveness Analysis by Technology, 2016-2032
- Figure 111: APAC Generative AI in Agriculture Market Revenue (US$ Mn) Market Share by End-Userin 2022
- Figure 112: APAC Generative AI in Agriculture Market Attractiveness Analysis by End-User, 2016-2032
- Figure 113: APAC Generative AI in Agriculture Market Revenue (US$ Mn) Market Share by Country in 2022
- Figure 114: APAC Generative AI in Agriculture Market Attractiveness Analysis by Country, 2016-2032
- Figure 115: APAC Generative AI in Agriculture Market Revenue (US$ Mn) (2016-2032)
- Figure 116: APAC Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Country (2016-2032)
- Figure 117: APAC Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Crop Type (2016-2032)
- Figure 118: APAC Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Application (2016-2032)
- Figure 119: APAC Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Technology (2016-2032)
- Figure 120: APAC Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by End-User (2016-2032)
- Figure 121: APAC Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Country (2016-2032)
- Figure 122: APAC Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Crop Type (2016-2032)
- Figure 123: APAC Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Application (2016-2032)
- Figure 124: APAC Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Technology (2016-2032)
- Figure 125: APAC Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by End-User (2016-2032)
- Figure 126: APAC Generative AI in Agriculture Market Share Comparison by Country (2016-2032)
- Figure 127: APAC Generative AI in Agriculture Market Share Comparison by Crop Type (2016-2032)
- Figure 128: APAC Generative AI in Agriculture Market Share Comparison by Application (2016-2032)
- Figure 129: APAC Generative AI in Agriculture Market Share Comparison by Technology (2016-2032)
- Figure 130: APAC Generative AI in Agriculture Market Share Comparison by End-User (2016-2032)
- Figure 131: Latin America Generative AI in Agriculture Market Revenue (US$ Mn) Market Share by Crop Typein 2022
- Figure 132: Latin America Generative AI in Agriculture Market Attractiveness Analysis by Crop Type, 2016-2032
- Figure 133: Latin America Generative AI in Agriculture Market Revenue (US$ Mn) Market Share by Applicationin 2022
- Figure 134: Latin America Generative AI in Agriculture Market Attractiveness Analysis by Application, 2016-2032
- Figure 135: Latin America Generative AI in Agriculture Market Revenue (US$ Mn) Market Share by Technologyin 2022
- Figure 136: Latin America Generative AI in Agriculture Market Attractiveness Analysis by Technology, 2016-2032
- Figure 137: Latin America Generative AI in Agriculture Market Revenue (US$ Mn) Market Share by End-Userin 2022
- Figure 138: Latin America Generative AI in Agriculture Market Attractiveness Analysis by End-User, 2016-2032
- Figure 139: Latin America Generative AI in Agriculture Market Revenue (US$ Mn) Market Share by Country in 2022
- Figure 140: Latin America Generative AI in Agriculture Market Attractiveness Analysis by Country, 2016-2032
- Figure 141: Latin America Generative AI in Agriculture Market Revenue (US$ Mn) (2016-2032)
- Figure 142: Latin America Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Country (2016-2032)
- Figure 143: Latin America Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Crop Type (2016-2032)
- Figure 144: Latin America Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Application (2016-2032)
- Figure 145: Latin America Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Technology (2016-2032)
- Figure 146: Latin America Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by End-User (2016-2032)
- Figure 147: Latin America Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Country (2016-2032)
- Figure 148: Latin America Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Crop Type (2016-2032)
- Figure 149: Latin America Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Application (2016-2032)
- Figure 150: Latin America Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Technology (2016-2032)
- Figure 151: Latin America Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by End-User (2016-2032)
- Figure 152: Latin America Generative AI in Agriculture Market Share Comparison by Country (2016-2032)
- Figure 153: Latin America Generative AI in Agriculture Market Share Comparison by Crop Type (2016-2032)
- Figure 154: Latin America Generative AI in Agriculture Market Share Comparison by Application (2016-2032)
- Figure 155: Latin America Generative AI in Agriculture Market Share Comparison by Technology (2016-2032)
- Figure 156: Latin America Generative AI in Agriculture Market Share Comparison by End-User (2016-2032)
- Figure 157: Middle East & Africa Generative AI in Agriculture Market Revenue (US$ Mn) Market Share by Crop Typein 2022
- Figure 158: Middle East & Africa Generative AI in Agriculture Market Attractiveness Analysis by Crop Type, 2016-2032
- Figure 159: Middle East & Africa Generative AI in Agriculture Market Revenue (US$ Mn) Market Share by Applicationin 2022
- Figure 160: Middle East & Africa Generative AI in Agriculture Market Attractiveness Analysis by Application, 2016-2032
- Figure 161: Middle East & Africa Generative AI in Agriculture Market Revenue (US$ Mn) Market Share by Technologyin 2022
- Figure 162: Middle East & Africa Generative AI in Agriculture Market Attractiveness Analysis by Technology, 2016-2032
- Figure 163: Middle East & Africa Generative AI in Agriculture Market Revenue (US$ Mn) Market Share by End-Userin 2022
- Figure 164: Middle East & Africa Generative AI in Agriculture Market Attractiveness Analysis by End-User, 2016-2032
- Figure 165: Middle East & Africa Generative AI in Agriculture Market Revenue (US$ Mn) Market Share by Country in 2022
- Figure 166: Middle East & Africa Generative AI in Agriculture Market Attractiveness Analysis by Country, 2016-2032
- Figure 167: Middle East & Africa Generative AI in Agriculture Market Revenue (US$ Mn) (2016-2032)
- Figure 168: Middle East & Africa Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Country (2016-2032)
- Figure 169: Middle East & Africa Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Crop Type (2016-2032)
- Figure 170: Middle East & Africa Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Application (2016-2032)
- Figure 171: Middle East & Africa Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Technology (2016-2032)
- Figure 172: Middle East & Africa Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by End-User (2016-2032)
- Figure 173: Middle East & Africa Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Country (2016-2032)
- Figure 174: Middle East & Africa Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Crop Type (2016-2032)
- Figure 175: Middle East & Africa Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Application (2016-2032)
- Figure 176: Middle East & Africa Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Technology (2016-2032)
- Figure 177: Middle East & Africa Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by End-User (2016-2032)
- Figure 178: Middle East & Africa Generative AI in Agriculture Market Share Comparison by Country (2016-2032)
- Figure 179: Middle East & Africa Generative AI in Agriculture Market Share Comparison by Crop Type (2016-2032)
- Figure 180: Middle East & Africa Generative AI in Agriculture Market Share Comparison by Application (2016-2032)
- Figure 181: Middle East & Africa Generative AI in Agriculture Market Share Comparison by Technology (2016-2032)
- Figure 182: Middle East & Africa Generative AI in Agriculture Market Share Comparison by End-User (2016-2032)
- List of Tables
- Table 1: Global Generative AI in Agriculture Market Comparison by Crop Type (2016-2032)
- Table 2: Global Generative AI in Agriculture Market Comparison by Application (2016-2032)
- Table 3: Global Generative AI in Agriculture Market Comparison by Technology (2016-2032)
- Table 4: Global Generative AI in Agriculture Market Comparison by End-User (2016-2032)
- Table 5: Global Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Region (2016-2032)
- Table 6: Global Generative AI in Agriculture Market Revenue (US$ Mn) (2016-2032)
- Table 7: Global Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Region (2016-2032)
- Table 8: Global Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Crop Type (2016-2032)
- Table 9: Global Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Application (2016-2032)
- Table 10: Global Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Technology (2016-2032)
- Table 11: Global Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by End-User (2016-2032)
- Table 12: Global Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Region (2016-2032)
- Table 13: Global Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Crop Type (2016-2032)
- Table 14: Global Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Application (2016-2032)
- Table 15: Global Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Technology (2016-2032)
- Table 16: Global Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by End-User (2016-2032)
- Table 17: Global Generative AI in Agriculture Market Share Comparison by Region (2016-2032)
- Table 18: Global Generative AI in Agriculture Market Share Comparison by Crop Type (2016-2032)
- Table 19: Global Generative AI in Agriculture Market Share Comparison by Application (2016-2032)
- Table 20: Global Generative AI in Agriculture Market Share Comparison by Technology (2016-2032)
- Table 21: Global Generative AI in Agriculture Market Share Comparison by End-User (2016-2032)
- Table 22: North America Generative AI in Agriculture Market Comparison by Application (2016-2032)
- Table 23: North America Generative AI in Agriculture Market Comparison by Technology (2016-2032)
- Table 24: North America Generative AI in Agriculture Market Comparison by End-User (2016-2032)
- Table 25: North America Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Country (2016-2032)
- Table 26: North America Generative AI in Agriculture Market Revenue (US$ Mn) (2016-2032)
- Table 27: North America Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Country (2016-2032)
- Table 28: North America Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Crop Type (2016-2032)
- Table 29: North America Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Application (2016-2032)
- Table 30: North America Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Technology (2016-2032)
- Table 31: North America Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by End-User (2016-2032)
- Table 32: North America Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Country (2016-2032)
- Table 33: North America Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Crop Type (2016-2032)
- Table 34: North America Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Application (2016-2032)
- Table 35: North America Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Technology (2016-2032)
- Table 36: North America Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by End-User (2016-2032)
- Table 37: North America Generative AI in Agriculture Market Share Comparison by Country (2016-2032)
- Table 38: North America Generative AI in Agriculture Market Share Comparison by Crop Type (2016-2032)
- Table 39: North America Generative AI in Agriculture Market Share Comparison by Application (2016-2032)
- Table 40: North America Generative AI in Agriculture Market Share Comparison by Technology (2016-2032)
- Table 41: North America Generative AI in Agriculture Market Share Comparison by End-User (2016-2032)
- Table 42: Western Europe Generative AI in Agriculture Market Comparison by Crop Type (2016-2032)
- Table 43: Western Europe Generative AI in Agriculture Market Comparison by Application (2016-2032)
- Table 44: Western Europe Generative AI in Agriculture Market Comparison by Technology (2016-2032)
- Table 45: Western Europe Generative AI in Agriculture Market Comparison by End-User (2016-2032)
- Table 46: Western Europe Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Country (2016-2032)
- Table 47: Western Europe Generative AI in Agriculture Market Revenue (US$ Mn) (2016-2032)
- Table 48: Western Europe Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Country (2016-2032)
- Table 49: Western Europe Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Crop Type (2016-2032)
- Table 50: Western Europe Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Application (2016-2032)
- Table 51: Western Europe Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Technology (2016-2032)
- Table 52: Western Europe Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by End-User (2016-2032)
- Table 53: Western Europe Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Country (2016-2032)
- Table 54: Western Europe Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Crop Type (2016-2032)
- Table 55: Western Europe Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Application (2016-2032)
- Table 56: Western Europe Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Technology (2016-2032)
- Table 57: Western Europe Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by End-User (2016-2032)
- Table 58: Western Europe Generative AI in Agriculture Market Share Comparison by Country (2016-2032)
- Table 59: Western Europe Generative AI in Agriculture Market Share Comparison by Crop Type (2016-2032)
- Table 60: Western Europe Generative AI in Agriculture Market Share Comparison by Application (2016-2032)
- Table 61: Western Europe Generative AI in Agriculture Market Share Comparison by Technology (2016-2032)
- Table 62: Western Europe Generative AI in Agriculture Market Share Comparison by End-User (2016-2032)
- Table 63: Eastern Europe Generative AI in Agriculture Market Comparison by Crop Type (2016-2032)
- Table 64: Eastern Europe Generative AI in Agriculture Market Comparison by Application (2016-2032)
- Table 65: Eastern Europe Generative AI in Agriculture Market Comparison by Technology (2016-2032)
- Table 66: Eastern Europe Generative AI in Agriculture Market Comparison by End-User (2016-2032)
- Table 67: Eastern Europe Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Country (2016-2032)
- Table 68: Eastern Europe Generative AI in Agriculture Market Revenue (US$ Mn) (2016-2032)
- Table 69: Eastern Europe Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Country (2016-2032)
- Table 70: Eastern Europe Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Crop Type (2016-2032)
- Table 71: Eastern Europe Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Application (2016-2032)
- Table 72: Eastern Europe Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Technology (2016-2032)
- Table 73: Eastern Europe Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by End-User (2016-2032)
- Table 74: Eastern Europe Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Country (2016-2032)
- Table 75: Eastern Europe Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Crop Type (2016-2032)
- Table 76: Eastern Europe Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Application (2016-2032)
- Table 77: Eastern Europe Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Technology (2016-2032)
- Table 78: Eastern Europe Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by End-User (2016-2032)
- Table 79: Eastern Europe Generative AI in Agriculture Market Share Comparison by Country (2016-2032)
- Table 80: Eastern Europe Generative AI in Agriculture Market Share Comparison by Crop Type (2016-2032)
- Table 81: Eastern Europe Generative AI in Agriculture Market Share Comparison by Application (2016-2032)
- Table 82: Eastern Europe Generative AI in Agriculture Market Share Comparison by Technology (2016-2032)
- Table 83: Eastern Europe Generative AI in Agriculture Market Share Comparison by End-User (2016-2032)
- Table 84: APAC Generative AI in Agriculture Market Comparison by Crop Type (2016-2032)
- Table 85: APAC Generative AI in Agriculture Market Comparison by Application (2016-2032)
- Table 86: APAC Generative AI in Agriculture Market Comparison by Technology (2016-2032)
- Table 87: APAC Generative AI in Agriculture Market Comparison by End-User (2016-2032)
- Table 88: APAC Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Country (2016-2032)
- Table 89: APAC Generative AI in Agriculture Market Revenue (US$ Mn) (2016-2032)
- Table 90: APAC Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Country (2016-2032)
- Table 91: APAC Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Crop Type (2016-2032)
- Table 92: APAC Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Application (2016-2032)
- Table 93: APAC Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Technology (2016-2032)
- Table 94: APAC Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by End-User (2016-2032)
- Table 95: APAC Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Country (2016-2032)
- Table 96: APAC Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Crop Type (2016-2032)
- Table 97: APAC Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Application (2016-2032)
- Table 98: APAC Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Technology (2016-2032)
- Table 99: APAC Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by End-User (2016-2032)
- Table 100: APAC Generative AI in Agriculture Market Share Comparison by Country (2016-2032)
- Table 101: APAC Generative AI in Agriculture Market Share Comparison by Crop Type (2016-2032)
- Table 102: APAC Generative AI in Agriculture Market Share Comparison by Application (2016-2032)
- Table 103: APAC Generative AI in Agriculture Market Share Comparison by Technology (2016-2032)
- Table 104: APAC Generative AI in Agriculture Market Share Comparison by End-User (2016-2032)
- Table 105: Latin America Generative AI in Agriculture Market Comparison by Crop Type (2016-2032)
- Table 106: Latin America Generative AI in Agriculture Market Comparison by Application (2016-2032)
- Table 107: Latin America Generative AI in Agriculture Market Comparison by Technology (2016-2032)
- Table 108: Latin America Generative AI in Agriculture Market Comparison by End-User (2016-2032)
- Table 109: Latin America Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Country (2016-2032)
- Table 110: Latin America Generative AI in Agriculture Market Revenue (US$ Mn) (2016-2032)
- Table 111: Latin America Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Country (2016-2032)
- Table 112: Latin America Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Crop Type (2016-2032)
- Table 113: Latin America Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Application (2016-2032)
- Table 114: Latin America Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Technology (2016-2032)
- Table 115: Latin America Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by End-User (2016-2032)
- Table 116: Latin America Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Country (2016-2032)
- Table 117: Latin America Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Crop Type (2016-2032)
- Table 118: Latin America Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Application (2016-2032)
- Table 119: Latin America Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Technology (2016-2032)
- Table 120: Latin America Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by End-User (2016-2032)
- Table 121: Latin America Generative AI in Agriculture Market Share Comparison by Country (2016-2032)
- Table 122: Latin America Generative AI in Agriculture Market Share Comparison by Crop Type (2016-2032)
- Table 123: Latin America Generative AI in Agriculture Market Share Comparison by Application (2016-2032)
- Table 124: Latin America Generative AI in Agriculture Market Share Comparison by Technology (2016-2032)
- Table 125: Latin America Generative AI in Agriculture Market Share Comparison by End-User (2016-2032)
- Table 126: Middle East & Africa Generative AI in Agriculture Market Comparison by Crop Type (2016-2032)
- Table 127: Middle East & Africa Generative AI in Agriculture Market Comparison by Application (2016-2032)
- Table 128: Middle East & Africa Generative AI in Agriculture Market Comparison by Technology (2016-2032)
- Table 129: Middle East & Africa Generative AI in Agriculture Market Comparison by End-User (2016-2032)
- Table 130: Middle East & Africa Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Country (2016-2032)
- Table 131: Middle East & Africa Generative AI in Agriculture Market Revenue (US$ Mn) (2016-2032)
- Table 132: Middle East & Africa Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Country (2016-2032)
- Table 133: Middle East & Africa Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Crop Type (2016-2032)
- Table 134: Middle East & Africa Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Application (2016-2032)
- Table 135: Middle East & Africa Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by Technology (2016-2032)
- Table 136: Middle East & Africa Generative AI in Agriculture Market Revenue (US$ Mn) Comparison by End-User (2016-2032)
- Table 137: Middle East & Africa Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Country (2016-2032)
- Table 138: Middle East & Africa Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Crop Type (2016-2032)
- Table 139: Middle East & Africa Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Application (2016-2032)
- Table 140: Middle East & Africa Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by Technology (2016-2032)
- Table 141: Middle East & Africa Generative AI in Agriculture Market Y-o-Y Growth Rate Comparison by End-User (2016-2032)
- Table 142: Middle East & Africa Generative AI in Agriculture Market Share Comparison by Country (2016-2032)
- Table 143: Middle East & Africa Generative AI in Agriculture Market Share Comparison by Crop Type (2016-2032)
- Table 144: Middle East & Africa Generative AI in Agriculture Market Share Comparison by Application (2016-2032)
- Table 145: Middle East & Africa Generative AI in Agriculture Market Share Comparison by Technology (2016-2032)
- Table 146: Middle East & Africa Generative AI in Agriculture Market Share Comparison by End-User (2016-2032)
- 1. Executive Summary
-
- IBM Corp.
- Microsoft Corp.
- John Deere
- The Climate Corporation (a subsidiary of Bayer)
- Ag Leader Technology
- Trimble Inc.
- Prospera Technologies
- Descartes Labs
- Taranis
- Granular (a Corteva Agriscience company)
- Other Key Players