Artificial Intelligence (AI) in Agriculture Market Size, Share, By Application (Precision Farming, Livestock Monitoring, Drone Analytics, and Agriculture Robots), By Technology (Machine Learning, Computer Vision, and Predictive Analytics), By Offering (Hardware, Software, AI-as-a-Service, and Service) and By Region - Trends, Analysis and Forecast till 2034

Artificial Intelligence (AI) in agriculture market size was valued at USD 12.2 Billion in 2024 and is expected to reach USD 21.3 Billion by 2034 growing at a CAGR of 18%

AI is changing the agricultural industry by improving productivity, efficiency, and sustainability. AI-driven technologies are employed in precision agriculture, analyzing data from sensors, drones, and satellites to enhance crop management. This assists in figuring out the optimal times for planting, watering, and harvesting, as well as pinpointing areas requiring care, like those impacted by pests or diseases.

AI is also involved in automatically sorting and grading produce, resulting in lower labor costs and enhanced consistency. Machine learning algorithms are able to forecast weather conditions, market needs, and crop productivity, enabling farmers to make well-informed choices. Furthermore, AI-powered robots and equipment are employed for activities such as planting, removing weeds, and collecting crops, leading to significant advantages in dealing with deficiencies in workforce. Moreover, AI improves supply chain management by forecasting market trends, guaranteeing optimal produce is delivered to the market promptly, ultimately decreasing wastage. AI's capacity to rapidly and accurately analyze large quantities of data makes it a potent instrument in enhancing food production, guaranteeing food security, and advocating for sustainable agricultural practices.

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Key Drivers of Target Market:

Growing Demand for Precision Farming

• As the world's population increases, the need for food also rises. Precision farming aids in meeting this need by optimizing crop yields and reducing waste, ensuring that food production matches population growth.

Technological advancements:

• AI and machine learning advancements have allowed for the analysis of extensive datasets, such as soil conditions, weather information, and satellite images. These technologies support decision-making tools that give farmers immediate insights, enhancing all farming operations.

Restrains:

High Cost:

• Implementing AI-driven technologies in agriculture requires significant investment in equipment, software, and training. For many small and medium-sized farms, the upfront costs can be prohibitive.

The market is segmented based on Application, Technology, Offering, and Region.

Application Insights:

• Precision Farming: Precision farming, or precision agriculture, utilizes cutting-edge technologies such as GPS, sensors, and data analysis to enhance crop yields. Farmers can make knowledgeable choices about planting, irrigation, fertilization, and pest control by assessing soil conditions, weather patterns, and crop health. This method reduces resource wastage, boosts crop production, and promotes sustainability by using water and fertilizers at specific times and locations to maximize efficiency.
• Livestock Monitoring: Monitoring livestock utilizes IoT devices, sensors, and AI to observe the real-time health, behavior, and productivity of animals. These advancements can oversee essential signals, identify illnesses in the early stages, and monitor movement behaviors, guaranteeing the well-being and proper care of livestock. This results in enhanced animal well-being, increased efficiency, and decreased expenses through illness prevention and improved feeding techniques.
• Drone Analytics: Utilizing drones with cameras and sensors to collect precise aerial information on crops and fields is known as drone analytics in agriculture. The information is then examined to evaluate the health of crops, identify pest infestations, track the growth of plants, and assess soil conditions. Drones offer farmers an aerial perspective of their fields, helping them swiftly pinpoint issues and implement precise solutions, ultimately enhancing productivity and crop output.
• Agriculture Robots: Agrobots, also known as agriculture robots, are self-operating machines created to carry out a range of farming duties like planting, weeding, harvesting, and organizing crops. These robots utilize artificial intelligence and machine learning to move through fields, distinguish between crops and weeds, and carry out tasks accurately. Agricultural robots cut labor expenses, boost effectiveness, and tackle labor deficiencies in the farming industry, leading to more scalable and productive farming processes.

Technology Insights:

• Machine Learning: In the field of agriculture, machine learning (ML) is employed to analyze extensive datasets, including weather patterns, soil conditions, and crop performance, in order to predict outcomes and enhance farming methods. Machine learning algorithms have the ability to enhance decision-making by analyzing past data, allowing for better timing in planting and forecasting pest infestations. This technology allows for more accurate and effective farming through constant improvement of models using new data.
• Computer Vision:  Computer Vision: Machines can understand and analyze visual information from the surroundings thanks to computer vision technology. In the field of agriculture, it is utilized for activities such as tracking crop health, recognizing weeds, and evaluating livestock conditions using image and video analysis. Drones and robots with computer vision capabilities can assess fields immediately, identifying problems that may be invisible to humans, thereby improving the precision and effectiveness of agricultural tasks.
• Predictive Analytics: Forecasting future results involves utilizing data, statistical algorithms, and machine learning techniques within Predictive Analytics. This technology is employed in agriculture to forecast crop production, weather patterns, pest outbreaks, and market trends. Predictive analytics assists farmers in making proactive decisions by offering information on potential future scenarios, which leads to risk reduction and resource use optimization.

Offering Insights:

• Hardware: AI-powered farming hardware includes physical devices such as sensors, drones, robots, and IoT devices that gather data and carry out tasks automatically. These tools are crucial for collecting live data and carrying out precise farming tasks. The success of AI in agriculture frequently relies on the caliber and functionalities of the equipment utilized in the field.
• Software: Software in agriculture entails the programs and systems that handle and interpret information gathered by machinery. This consists of AI algorithms, machine learning models, and farm management systems that offer advice and guidance to farmers. Software solutions help analyze huge data sets, transforming unprocessed data into actionable insights.
• AI-as-a-Service: AI-as-a-Service allows farmers to utilize AI tools and technologies through a subscription model, eliminating the requirement for a large initial investment in hardware or software. This system enables farmers to take advantage of modern AI features, like machine learning and predictive analytics, on cloud platforms, which makes high-tech tools more available and expandable.

Regional Insights

• North America: North America is one of the leading players in the AI in agriculture market worldwide, owing to the presence of a well-organized ecosystem for innovation and market development. The most important factors in the region are the well-developed R&D infrastructure and mature pharmaceutical and biotechnology industries, besides high levels of disposable income. Leading companies invest heavily in developing novel farming with better functionality and broader applications, continuously pushing the boundaries of farming technology.
• Asia Pacific: The highest growth in the global specialty farming market is witnessed in Asia. Several reasons trigger this growth. The pharmaceutical and biotechnology industries in this region are the fastest growing. Second, there is a growth in healthcare spending within the Asia Pacific. Lastly, there is an enhanced demand for processed foods in the region. Other than the above factors, governments of various countries in the region have been enacting policies and initiating funding programs to support and increase R&D activities in biotechnology; this indirectly impacts the specialty farming market.
• Europe: The AI in agriculture market is well-matured and developed in Europe, with strong innovation and regulatory emphasis. Europe's leading companies had always excelled in making high-quality, specialty farming for all applications. In addition, the sustainable approach of European industries to using green farming to produce biofuels and bioremediation will further add to the growth of this market. The AI in agriculture market for pharmaceuticals and farming diagnostics market segments is mature and, in many instances, even approaching saturation from established applications. Growth will only be significant from new food applications and the environmental sector.
• Latin America: The Latin American AI in agriculture market is emerging and promises high growth. The company has witnessed reasonable growth from different Technology for some time now. The moment the economies in the region start on a growing path, disposable income also goes up. This will increase the processed food industry and many others, like food, which heavily require farming. On the other hand, there is excellent awareness about health in Latin America, which consequently gives way to increasing demand for various diagnostic tests and treatments, including specialty farming.
• Middle East and Africa: MEA is yet another developing market for specialty farming, with the expansion being quite stifled due to certain constraints. On the other hand, the capability to produce AI tools is low in the MEA market. The region would heavily depend on imports from the rest of the world. Further, the regulatory frameworks for AI may vary substantially between countries in the MEA region.

AI in agriculture market Report Scope:

Segments Covered in the Report:

This report forecasts revenue growth at global, regional, and country levels and provides an analysis of the latest industry trends and opportunities in each of the sub-segments from 2024 to 2034. For the purpose of this study segmented the target market report based on Application, Technology, Application, and Region.

Segmentation:

By Application:

• Precision Farming,
• Livestock Monitoring
• Drone Analytics
• Agriculture Robots

By Technology:

• Machine Learning
• Computer Vision
• Predictive Analytics

By Offerings:

• Hardware
• Software
• Ai as a service

By Region:

• North America
  • U.S.
  • Canada
• Europe
  • Germany
  • UK
  • France
  • Russia
  • Italy
  • Rest of Europe
• Asia Pacific
  • China
  • India
  • Japan
  • South Korea
  • Rest of Asia Pacific
• Latin America
  • Brazil
  • Mexico
  • Rest of Latin America
• Middle East & Africa
  • GCC
  • Israel
  • South Africa
  • Rest of Middle East & Africa

The key players operating the AI in agriculture market include Microsoft, IBM Corporation, Granular, Inc., AgEagle Aerial Systems Inc., The Climate Corporation, Deere & Company, Descartes Labs Inc., Prospera Technologies, GAMAYA, aWhere Inc., Taranis, ec2ce, VineView, Precision Hawk, and Tule Technologies Inc.

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• Microsoft *
  • Company Overview
  • Product Portfolio
  • Key Highlights
  • Financial Performance
  • Business Strategies
• IBM Corporation
• Granular, Inc.
• AgEagle Aerial Systems Inc.
• The Climate Corporation
• Deere & Company
• Descartes Labs Inc.
• Prospera Technologies
• GAMAYA
• aWhere Inc.
• Taranis
• ec2ce
• VineView
• Precision Hawk
• Tule Technologies Inc.

“*” marked represents similar segmentation in other categories in the respective section.

Research Objective and Assumption

• Research Objectives
• Assumptions
• Abbreviations

Market Preview

• Report Description
  • Market Definition and Scope
• Executive Summary
  • Market Snippet, By Application
  • Market Snippet, By Technology
  • Market Snippet, By Offering
  • Market Snippet, By Region
• Opportunity Map Analysis

Market Dynamics, Regulations, and Trends Analysis

• Market Dynamics
  • Drivers
  • Restraints
  • Market Opportunities
• Market Trends
• Product Launch
• Merger and Acquisitions
• Impact Analysis
• PEST Analysis
• Porter’s Analysis

Market Segmentation, Application, Forecast Period up to 10 Years, (USD Bn)

• Overview
  • Market Value and Forecast (USD Bn), and Share Analysis (%), Forecast Period up to 10 Years
  • Y-o-Y Growth Analysis (%), Forecast Period up to 10 Years
  • Segment Trends
• Precision Farming
  • Overview
  • Market Size and Forecast (USD Bn), and Y-o-Y Growth (%), Forecast Period up to 10 Years
• Livestock Monitoring
  • Overview
  • Market Size and Forecast (USD Bn), and Y-o-Y Growth (%), Forecast Period up to 10 Years
• Drone Analytics
  • Overview
  • Market Size and Forecast (USD Bn), and Y-o-Y Growth (%), Forecast Period up to 10 Years
• Agricultural Robots
  • Overview
  • Market Size and Forecast (USD Bn), and Y-o-Y Growth (%), Forecast Period up to 10 Years

Market Segmentation, Technology, Forecast Period up to 10 Years, (USD Bn)

• Overview
  • Market Value and Forecast (USD Bn), and Share Analysis (%), Forecast Period up to 10 Years
  • Y-o-Y Growth Analysis (%), Forecast Period up to 10 Years
  • Segment Trends
• Machine Learning
  • Overview
  • Market Size and Forecast (USD Bn), and Y-o-Y Growth (%), Forecast Period up to 10 Years
• Computer Vision
  • Overview
  • Market Size and Forecast (USD Bn), and Y-o-Y Growth (%), Forecast Period up to 10 Years
• Predictive Analytics
  • Overview
  • Market Size and Forecast (USD Bn), and Y-o-Y Growth (%), Forecast Period up to 10 Years

Market Segmentation, Offering, Forecast Period up to 10 Years, (USD Bn)

• Overview
  • Market Value and Forecast (USD Bn), and Share Analysis (%), Forecast Period up to 10 Years
  • Y-o-Y Growth Analysis (%), Forecast Period up to 10 Years
  • Segment Trends
• Hardware
  • Overview
  • Market Size and Forecast (USD Bn), and Y-o-Y Growth (%), Forecast Period up to 10 Years
• Software
  • Overview
  • Market Size and Forecast (USD Bn), and Y-o-Y Growth (%), Forecast Period up to 10 Years
• Ai as a service
  • Overview
  • Market Size and Forecast (USD Bn), and Y-o-Y Growth (%), Forecast Period up to 10 Years

Market Segmentation, By Region, Forecast Period up to 10 Years, (USD Bn)

• Overview
  • Market Value and Forecast (USD Bn), and Share Analysis (%), Forecast Period up to 10 Years
  • Y-o-Y Growth Analysis (%), Forecast Period up to 10 Years
  • Regional Trends
• North America
  • Market Size and Forecast (USD Bn), By Application, Forecast Period up to 10 Years
  • Market Size and Forecast (USD Bn), By Technology, Forecast Period up to 10 Years
  • Market Size and Forecast (USD Bn), By Offering, Forecast Period up to 10 Years
  • Market Size and Forecast (USD Bn), By Country, Forecast Period up to 10 Years
    • U.S
    • Canada
• Asia Pacific
  • Market Size and Forecast (USD Bn), By Application, Forecast Period up to 10 Years
  • Market Size and Forecast (USD Bn), By Technology, Forecast Period up to 10 Years
  • Market Size and Forecast (USD Bn), By Offering, Forecast Period up to 10 Years
  • Market Size and Forecast (USD Bn), By Country, Forecast Period up to 10 Years
    • India
    • Japan
    • South Korea
    • China
    • Rest of Asia Pacific
• Europe
  • Market Size and Forecast (USD Bn), By Application, Forecast Period up to 10 Years
  • Market Size and Forecast (USD Bn), By Technology, Forecast Period up to 10 Years
  • Market Size and Forecast (USD Bn), By Offering, Forecast Period up to 10 Years
  • Market Size and Forecast (USD Bn), By Country, Forecast Period up to 10 Years
    • UK
    • Germany
    • France
    • Russia
    • Italy
    • Rest of Europe
• Latin America
  • Market Size and Forecast (USD Bn), By Application, Forecast Period up to 10 Years
  • Market Size and Forecast (USD Bn), By Technology, Forecast Period up to 10 Years
  • Market Size and Forecast (USD Bn), By Offering, Forecast Period up to 10 Years
  • Market Size and Forecast (USD Bn), By Country, Forecast Period up to 10 Years
    • Brazil
    • Mexico
    • Rest of Latin America
• Middle East and Africa
  • Market Size and Forecast (USD Bn), By Application, Forecast Period up to 10 Years
  • Market Size and Forecast (USD Bn), By Technology, Forecast Period up to 10 Years
  • Market Size and Forecast (USD Bn), By Offering, Forecast Period up to 10 Years
  • Market Size and Forecast (USD Bn), By Country, Forecast Period up to 10 Years
    • GCC
    • Israel
    • South Africa
    • Rest of Middle East and Africa

Competitive Landscape

• Heat Map Analysis
• Company Profiles

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

The Last Word

• Future Impact
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