AI in Agriculture Market
Product Overview
Artificial Intelligence in Agriculture uses modern and innovative agricultural technologies timprove productivity and yield tdeliver better and more efficient farming services. Using specific equipment such as the Internet of Thing models, sensors and actuators, geo-positioning systems, Unmanned Aerial Vehicles (UAVs or drones), robotics & fertilizers, irrigation management, and son, farmers can advance their production and harvest by controlling pests, increasing productivity, monitoring the soil quality while reducing the time, energy and work needed for these tasks. Artificial Intelligence in agriculture helps and assists in evaluating and taking decisions tboost crop growth and production. In agriculture, artificial intelligence has a variety of uses, including agricultural automation, digital water network systems, face recognition, and tractors without a driver. One of the important factors that boost the market for artificial intelligence in agriculture is the increase in usage of AI and the need for better yields of goods.
Market Highlights
Factors such as growing stress on the food supply chain due texponentially increasing population, rising implementation of the Internet of Things in the agricultural sector, improving the standard of living, growing focus on enhanced crop monitoring, and increased demand for higher agricultural yield, are driving growth in the artificial intelligence market. Moreover, limited land for agriculture coupled with supportive government policies tencourage the use of AI technologies is anticipated tfuel the market growth. Nonetheless, insufficient knowledge of high technology machine learning solutions in agriculture can hamper the growth of artificial intelligence in the agriculture market. However, the increased use of drones in farms is expected taccelerate the deployment of artificial intelligence in the agriculture market.
Global Artificial Intelligence in Agriculture Market Analysis
AI in Agriculture Market
Global Artificial Intelligence in Agriculture Market: Segments
Software offerings are anticipated tbe the fastest-growing over 2020-2030
Based on offerings, the global AI in Agriculture Market is segmented inthardware, software, and services. The software segment captured a significant share in 2019 and is projected thave the highest CAGR during the forecast period. The convergence of digital technology with agriculture techniques, increased adoption of automation and control systems, such as GPS / GNSS receivers, irrigation controls, guidance & steering systems, and the demand for database management systems has created a new approach tfarming practices that stimulates market growth.
AI in Agriculture Market
Machine Learning Market tdrive the use of AI in agriculture during the forecast period
Based on technology, AI in the agriculture market is categorized intmachine learning, predictive analytics, and computer vision. The machine learning segment accounted for a major share in 2019 and is expected tgrow at a CAGR of XX% during the forecast period. Machine-learning technologies for increasing yields and gaining a competitive advantage in business activities are embraced by farming organizations and farmers worldwide. Machine learning is anticipated texpand exponentially different agricultural practices over the forecast timeframe. Furthermore, the application of computer education tsensor data expands the potential of production enhancement and turns farm management systems inttrue artificial intelligence systems. Hence, the machine learning segment is expected texpand.
AI in Agriculture Market
Precision farming application thold significant market share during 2020-2030
Global AI in the agriculture market is segregated by application intlivestock monitoring application, precision farming application, agriculture robot’s application, drone analytics application, and others. The precision farming application accounted for a share of XX% in 2019 and is projected thold a significant share in 2020-30 owing tthe growing popularity of the precision farming method amongst farmers as a result of the need tmaximize production with the available scarce resources and treduce costs of cultivation. Also, the ability of IoT-based systems in field mapping and management are utilized by agricultural managers and manufacturers, which alscontribute trapid market development.
AI in Agriculture Market
Market Dynamics
Drivers
Rising demand for Agricultural Produce
Growing global demand for food, farmers need tincrease crop production either by increasing the amount of agricultural land or by adopting advanced agricultural methods such as precision farming. Another major factor that has prompted farmers timplement digital farming solutions in their farms tboost the productivity of agricultural land is the increased demand for quality crops that meet the increasing requirements of grains and plants.
Restraints
High Equipment Cost
Some of the factors limiting the growth of Artificial Intelligence in the agriculture market are the high cost of devices used in Artificial Intelligence in agriculture and the lack of awareness among farmers. High costs incurred in the production of Artificial Intelligence in agricultural equipment, in turn, increase the price of the final product, which is likely trestrict the growth of the market over the forecast period.
Global Artificial Intelligence in Agriculture Market: Region
Global Artificial Intelligence in Agriculture market is segmented based on regional analysis intfive major regions. These include North America, Latin America, Europe, Asia-Pacific, and the rest of the world is classified as Middle-East and Africa.
North America tregister a remarkable CAGR during the forecast period
Owing tthe concentration of leading industrial automation players and the introduction of artificial intelligence technologies in North America, the share in 2019 accounted for more than other regions. North America is marked by an enhanced standard of living of the people, continuous technological investments, major IoT investments, and growing policy emphasis on the development of in-house AI equipment. These factors are likely tboost growth shortly.
AI in Agriculture Market
Global Artificial Intelligence in the Agriculture market is further segmented by region into:
North America Market Size, Share, Trends, Opportunities, Y-o-Y Growth, CAGR- United States and Canada
Latin America Market Size, Share, Trends, Opportunities, Y-o-Y Growth, CAGR- Mexico, Argentina, Brazil and Rest of Latin America
Europe Market Size, Share, Trends, Opportunities, Y-o-Y Growth, CAGR- UK, Germany, France, Italy, Spain, Belgium, Hungary, Luxembourg, Netherlands, Poland, NORDIC, Russia, Turkey and Rest of Europe
Asia-Pacific Market Size, Share, Trends, Opportunities, Y-o-Y Growth, CAGR- India, China, South Korea, Malaysia, Japan, Indonesia, Australia, New Zealand, and Rest of Asia-Pacific
Middle East and Africa Market Size, Share, Trends, Opportunities, Y-o-Y Growth, CAGR- North Africa, Israel, GCC, South Africa and Rest of Middle East and Africa
Global Artificial Intelligence in Agriculture Market: Key Players
Microsoft Corporation
Company overview, Business Strategy, Key Product Offerings, Financial Performance, Key Performance Indicators, Risk Analysis, Recent Development, Regional Presence, SWOT Analysis
Precision Hawk
Deere & Company
The Climate Corporation
International Business Machines Corp.
Farmers Edge Inc.
AgEagle Aerial Systems
Gamaya Inc
Descartes Lab Inc.
Prospera Technologies
Global Artificial Intelligence in Agriculture Market Report alscontains an analysis of:
Artificial Intelligence in Agriculture Market by segment
By Offering
Hardware
Software
Services
By Application
Livestock Monitoring Application
Precision Farming Application
Agriculture Robots Application
Drone Analytics Application
Others
By Region
North America
Latin America
Europe
Asia-Pacific
Middle East and Africa
Artificial Intelligence in Agriculture Market Size
Artificial Intelligence in Agriculture Market Dynamics
Supply and Demand
Current Issues/trends/challenges
Competition and Companies Involved in the Market
Value Chain of the Market
Market Drivers and Restraints
Artificial Intelligence in Agriculture uses modern and innovative agricultural technologies timprove productivity and yield tdeliver better and more efficient farming services. Using specific equipment such as the Internet of Thing models, sensors and actuators, geo-positioning systems, Unmanned Aerial Vehicles (UAVs or drones), robotics & fertilizers, irrigation management, and son, farmers can advance their production and harvest by controlling pests, increasing productivity, monitoring the soil quality while reducing the time, energy and work needed for these tasks. Artificial Intelligence in agriculture helps and assists in evaluating and taking decisions tboost crop growth and production. In agriculture, artificial intelligence has a variety of uses, including agricultural automation, digital water network systems, face recognition, and tractors without a driver. One of the important factors that boost the market for artificial intelligence in agriculture is the increase in usage of AI and the need for better yields of goods.
Market Highlights
Factors such as growing stress on the food supply chain due texponentially increasing population, rising implementation of the Internet of Things in the agricultural sector, improving the standard of living, growing focus on enhanced crop monitoring, and increased demand for higher agricultural yield, are driving growth in the artificial intelligence market. Moreover, limited land for agriculture coupled with supportive government policies tencourage the use of AI technologies is anticipated tfuel the market growth. Nonetheless, insufficient knowledge of high technology machine learning solutions in agriculture can hamper the growth of artificial intelligence in the agriculture market. However, the increased use of drones in farms is expected taccelerate the deployment of artificial intelligence in the agriculture market.
Global Artificial Intelligence in Agriculture Market Analysis
AI in Agriculture Market
Global Artificial Intelligence in Agriculture Market: Segments
Software offerings are anticipated tbe the fastest-growing over 2020-2030
Based on offerings, the global AI in Agriculture Market is segmented inthardware, software, and services. The software segment captured a significant share in 2019 and is projected thave the highest CAGR during the forecast period. The convergence of digital technology with agriculture techniques, increased adoption of automation and control systems, such as GPS / GNSS receivers, irrigation controls, guidance & steering systems, and the demand for database management systems has created a new approach tfarming practices that stimulates market growth.
AI in Agriculture Market
Machine Learning Market tdrive the use of AI in agriculture during the forecast period
Based on technology, AI in the agriculture market is categorized intmachine learning, predictive analytics, and computer vision. The machine learning segment accounted for a major share in 2019 and is expected tgrow at a CAGR of XX% during the forecast period. Machine-learning technologies for increasing yields and gaining a competitive advantage in business activities are embraced by farming organizations and farmers worldwide. Machine learning is anticipated texpand exponentially different agricultural practices over the forecast timeframe. Furthermore, the application of computer education tsensor data expands the potential of production enhancement and turns farm management systems inttrue artificial intelligence systems. Hence, the machine learning segment is expected texpand.
AI in Agriculture Market
Precision farming application thold significant market share during 2020-2030
Global AI in the agriculture market is segregated by application intlivestock monitoring application, precision farming application, agriculture robot’s application, drone analytics application, and others. The precision farming application accounted for a share of XX% in 2019 and is projected thold a significant share in 2020-30 owing tthe growing popularity of the precision farming method amongst farmers as a result of the need tmaximize production with the available scarce resources and treduce costs of cultivation. Also, the ability of IoT-based systems in field mapping and management are utilized by agricultural managers and manufacturers, which alscontribute trapid market development.
AI in Agriculture Market
Market Dynamics
Drivers
Rising demand for Agricultural Produce
Growing global demand for food, farmers need tincrease crop production either by increasing the amount of agricultural land or by adopting advanced agricultural methods such as precision farming. Another major factor that has prompted farmers timplement digital farming solutions in their farms tboost the productivity of agricultural land is the increased demand for quality crops that meet the increasing requirements of grains and plants.
Restraints
High Equipment Cost
Some of the factors limiting the growth of Artificial Intelligence in the agriculture market are the high cost of devices used in Artificial Intelligence in agriculture and the lack of awareness among farmers. High costs incurred in the production of Artificial Intelligence in agricultural equipment, in turn, increase the price of the final product, which is likely trestrict the growth of the market over the forecast period.
Global Artificial Intelligence in Agriculture Market: Region
Global Artificial Intelligence in Agriculture market is segmented based on regional analysis intfive major regions. These include North America, Latin America, Europe, Asia-Pacific, and the rest of the world is classified as Middle-East and Africa.
North America tregister a remarkable CAGR during the forecast period
Owing tthe concentration of leading industrial automation players and the introduction of artificial intelligence technologies in North America, the share in 2019 accounted for more than other regions. North America is marked by an enhanced standard of living of the people, continuous technological investments, major IoT investments, and growing policy emphasis on the development of in-house AI equipment. These factors are likely tboost growth shortly.
AI in Agriculture Market
Global Artificial Intelligence in the Agriculture market is further segmented by region into:
North America Market Size, Share, Trends, Opportunities, Y-o-Y Growth, CAGR- United States and Canada
Latin America Market Size, Share, Trends, Opportunities, Y-o-Y Growth, CAGR- Mexico, Argentina, Brazil and Rest of Latin America
Europe Market Size, Share, Trends, Opportunities, Y-o-Y Growth, CAGR- UK, Germany, France, Italy, Spain, Belgium, Hungary, Luxembourg, Netherlands, Poland, NORDIC, Russia, Turkey and Rest of Europe
Asia-Pacific Market Size, Share, Trends, Opportunities, Y-o-Y Growth, CAGR- India, China, South Korea, Malaysia, Japan, Indonesia, Australia, New Zealand, and Rest of Asia-Pacific
Middle East and Africa Market Size, Share, Trends, Opportunities, Y-o-Y Growth, CAGR- North Africa, Israel, GCC, South Africa and Rest of Middle East and Africa
Global Artificial Intelligence in Agriculture Market: Key Players
Microsoft Corporation
Company overview, Business Strategy, Key Product Offerings, Financial Performance, Key Performance Indicators, Risk Analysis, Recent Development, Regional Presence, SWOT Analysis
Precision Hawk
Deere & Company
The Climate Corporation
International Business Machines Corp.
Farmers Edge Inc.
AgEagle Aerial Systems
Gamaya Inc
Descartes Lab Inc.
Prospera Technologies
Global Artificial Intelligence in Agriculture Market Report alscontains an analysis of:
Artificial Intelligence in Agriculture Market by segment
By Offering
Hardware
Software
Services
By Application
Livestock Monitoring Application
Precision Farming Application
Agriculture Robots Application
Drone Analytics Application
Others
By Region
North America
Latin America
Europe
Asia-Pacific
Middle East and Africa
Artificial Intelligence in Agriculture Market Size
Artificial Intelligence in Agriculture Market Dynamics
Supply and Demand
Current Issues/trends/challenges
Competition and Companies Involved in the Market
Value Chain of the Market
Market Drivers and Restraints
1. EXECUTIVE SUMMARY
2. GLOBAL AI IN AGRICULTURE MARKET
2.1. Product Overview
2.2. Market Definition
2.3. Segmentation
2.4. Assumptions and Acronyms
3. RESEARCH METHODOLOGY
3.1. Research Objectives
3.2. Primary Research
3.3. Secondary Research
3.4. Forecast Model
3.5. Market Size Estimation
4. AVERAGE PRICING ANALYSIS
5. MACRO-ECONOMIC INDICATORS
6. MARKET DYNAMICS
6.1. Growth Drivers
6.2. Restraints
6.3. Opportunity
6.4. Trends
7. CORRELATION & REGRESSION ANALYSIS
7.1. Correlation Matrix
7.2. Regression Matrix
8. RECENT DEVELOPMENT, POLICIES & REGULATORY LANDSCAPE
9. RISK ANALYSIS
9.1. Demand Risk Analysis
9.2. Supply Risk Analysis
10. GLOBAL AI IN AGRICULTURE MARKET ANALYSIS
10.1. Porters Five Forces
10.1.1. Threat of New Entrants
10.1.2. Bargaining Power of Suppliers
10.1.3. Threat of Substitutes
10.1.4. Rivalry
10.2. PEST Analysis
10.2.1. Political
10.2.2. Economic
10.2.3. Social
10.2.4. Technological
11. GLOBAL AI IN AGRICULTURE MARKET
11.1. Market Size & forecast, 2019A-2030F
11.1.1. By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
11.1.2. By Volume (Million Units) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
12. GLOBAL AI IN AGRICULTURE MARKET: MARKET SEGMENTATION
12.1. By Regions
12.1.1. North America:(U.S. and Canada)
12.1.1.1. By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
12.1.2. Europe: (Brazil, Mexico, Argentina, Rest of Latin America)
12.1.2.1. By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
12.1.3. Asia-Pacific: (Germany, UK, France, Italy, Spain, BENELUX, NORDIC, Hungary, Poland, Turkey, Russia, Rest of Europe)
12.1.3.1. By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
12.1.4. LATAM: (Brazil, South Africa, Saudi Arabia, U.A.E., and Other Countries)
12.1.4.1. By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
12.1.5. MEA: (Brazil, South Africa, Saudi Arabia, U.A.E., and Other Countries)
12.1.5.1. By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
12.2. By Type: Market Share (2020-2030F)
12.2.1. Product, By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
12.2.2. Service, By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
12.3. By Technology: Market Share (2020-2030F)
12.3.1. Machine Learning, By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
12.3.2. Computer Vision, By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
12.3.3. Predictive Analytics, By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
12.4. By Application: Market Share (2020-2030F)
12.4.1. Precision Farming, By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
12.4.2. Agricultural Robots, By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
12.4.3. Livestock Monitoring, By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
12.4.4. Drone Analytics, By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
13. COMPANY PROFILE
13.1. International Business Machines (IBM) Corporation
13.1.1. Company Overview
13.1.2. Company Total Revenue (Financials)
13.1.3. Market Potential
13.1.4. Global Presence
13.1.5. Key Performance Indicators
13.1.6. SWOT Analysis
13.1.7. Product Launch
13.2. Microsoft Corporation
13.3. Bayer AG
13.4. Deere & Company
13.5. A.A.A Taranis Visual Ltd.
13.6. AgEagle Aerial Systems Inc.
13.7. AGCO Corporation
13.8. Raven Industries Inc.
13.9. Ag Leader Technology
13.10. Trimble Inc.
13.11. Google LLC
13.12. Gamaya SA
13.13. Granular Inc.
13.14. Other Prominent Players
Consultant Recommendation
The above-given segmentation and companies could be subjected to further modification based on in-depth feasibility studies conducted for the final deliverable.
2. GLOBAL AI IN AGRICULTURE MARKET
2.1. Product Overview
2.2. Market Definition
2.3. Segmentation
2.4. Assumptions and Acronyms
3. RESEARCH METHODOLOGY
3.1. Research Objectives
3.2. Primary Research
3.3. Secondary Research
3.4. Forecast Model
3.5. Market Size Estimation
4. AVERAGE PRICING ANALYSIS
5. MACRO-ECONOMIC INDICATORS
6. MARKET DYNAMICS
6.1. Growth Drivers
6.2. Restraints
6.3. Opportunity
6.4. Trends
7. CORRELATION & REGRESSION ANALYSIS
7.1. Correlation Matrix
7.2. Regression Matrix
8. RECENT DEVELOPMENT, POLICIES & REGULATORY LANDSCAPE
9. RISK ANALYSIS
9.1. Demand Risk Analysis
9.2. Supply Risk Analysis
10. GLOBAL AI IN AGRICULTURE MARKET ANALYSIS
10.1. Porters Five Forces
10.1.1. Threat of New Entrants
10.1.2. Bargaining Power of Suppliers
10.1.3. Threat of Substitutes
10.1.4. Rivalry
10.2. PEST Analysis
10.2.1. Political
10.2.2. Economic
10.2.3. Social
10.2.4. Technological
11. GLOBAL AI IN AGRICULTURE MARKET
11.1. Market Size & forecast, 2019A-2030F
11.1.1. By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
11.1.2. By Volume (Million Units) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
12. GLOBAL AI IN AGRICULTURE MARKET: MARKET SEGMENTATION
12.1. By Regions
12.1.1. North America:(U.S. and Canada)
12.1.1.1. By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
12.1.2. Europe: (Brazil, Mexico, Argentina, Rest of Latin America)
12.1.2.1. By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
12.1.3. Asia-Pacific: (Germany, UK, France, Italy, Spain, BENELUX, NORDIC, Hungary, Poland, Turkey, Russia, Rest of Europe)
12.1.3.1. By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
12.1.4. LATAM: (Brazil, South Africa, Saudi Arabia, U.A.E., and Other Countries)
12.1.4.1. By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
12.1.5. MEA: (Brazil, South Africa, Saudi Arabia, U.A.E., and Other Countries)
12.1.5.1. By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
12.2. By Type: Market Share (2020-2030F)
12.2.1. Product, By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
12.2.2. Service, By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
12.3. By Technology: Market Share (2020-2030F)
12.3.1. Machine Learning, By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
12.3.2. Computer Vision, By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
12.3.3. Predictive Analytics, By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
12.4. By Application: Market Share (2020-2030F)
12.4.1. Precision Farming, By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
12.4.2. Agricultural Robots, By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
12.4.3. Livestock Monitoring, By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
12.4.4. Drone Analytics, By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
13. COMPANY PROFILE
13.1. International Business Machines (IBM) Corporation
13.1.1. Company Overview
13.1.2. Company Total Revenue (Financials)
13.1.3. Market Potential
13.1.4. Global Presence
13.1.5. Key Performance Indicators
13.1.6. SWOT Analysis
13.1.7. Product Launch
13.2. Microsoft Corporation
13.3. Bayer AG
13.4. Deere & Company
13.5. A.A.A Taranis Visual Ltd.
13.6. AgEagle Aerial Systems Inc.
13.7. AGCO Corporation
13.8. Raven Industries Inc.
13.9. Ag Leader Technology
13.10. Trimble Inc.
13.11. Google LLC
13.12. Gamaya SA
13.13. Granular Inc.
13.14. Other Prominent Players
Consultant Recommendation
The above-given segmentation and companies could be subjected to further modification based on in-depth feasibility studies conducted for the final deliverable.
