AI In Agriculture Market by Offering (Hardware, Software, Services), Technology (Machine Learning, NLP, Context-Aware Computing, Computer Vision), Technology (Machine Learning, Computer Vision, Predictive Analytics), Application (Precision Farming, Drone Analytics, Agriculture Robots, Livestock Monitoring), By Region (North America, Europe, Asia Pacific, Latin America, and Middle East & Africa); Trend Analysis, Competitive Market Share & Forecast, 2016-26
- Published Date: February 2020
- Report ID: BWC19397
- Available Format: PDF
- Page: 185
Report Overview
Global
AI in Agriculture Market Forecast and Trends
The global market of AI in
Agriculture anticipated to witness significant growth rate with a CAGR rise of
21.6% to reach USD 3,013 million by 2026, owing to growing demand for
agricultural production due to the growing population and increased adoption of
information management systems.
In addition advanced
technologies for improving crop productivity, increased crop productivity
through the introduction of in-depth learning techniques, and the initiatives
by governments around the world to promote the adoption of modern agricultural
techniques. The combination of the IoT’s and artificial intelligence
technologies such as machine learning, computer vision, and predictive
analytics further enables farmers to analyze real-time data on market weather,
temperature, soil moisture, plant health, and crop prices. The growing use and
growing need for better product yield were assessed as one of the key factors
that drive robots ' demand in agriculture.
Global
AI in Agriculture Market: Overview
Artificial Intelligence (AI)
is a program-based technology that enables digital computers and robots to
perform real-time tasks through the use of human cognitive intelligence such as
speech recognition, visual perception, decision making, etc. In addition AI is
commonly used in agriculture industry for precision cultivation, crop
monitoring, crop analytics, etc.
Artificial Intelligence has
different applications in agriculture sector including rural automations,
facial recognition, computerized water systems and driverless tractors. Such
implementations are performed concerning an alternate kind of AI-dependent
sensors, GPS systems, radars, and other cutting edge contraptions. AI is
receiving a fascinating reaction from investors all around considering these
broad applications. Human-made reasoning is one of those critical innovations
in advanced agriculture which is being updated and conveyed for more
sustainable use of available assets.
Growth
Drivers
Growing
demand for monitoring of livestock
Increasing demand for
livestock tracking is one of the key drivers of AI in the agricultural
industry. Livestock plays a key role in meeting the demand for meat, milk,
eggs, and wool. With changing lifestyles, growing population, and rising per
capita income levels, meat, eggs, and milk consumption are increasing globally.
In addition, to meet the demand for protein-rich foods, livestock health needs
to be regularly monitored. Through applying advanced AI technologies, such as
facial recognition for livestock and image classification combined with body
condition score and feeding habits, dairy farms can now track all behavioral
aspects of a herd individually.
Rising
adoption of IoT
Another major factor driving
AI in the agricultural market is the rising adoption of IoT. The IoT industry is
growing globally with the increasing use of mobile devices and cloud computing.
Different advantages provided by IoT, such as the ability to handle large
amounts of structured and unstructured data format, drive IoT demand in
agriculture sector.
Health
monitoring of crops
Together with hyperspectral
imaging and 3D laser scanning, remote sensing techniques are crucial for
creating crop metrics through thousands of acres. It has the likelihood of
leading revolutionary change in the way farmland is observed by farmers from
both the perspective of time and effort. It system will also be used to track
crops during their entire lifecycle that includes reporting in the event of
abnormalities.
Automation
techniques in irrigation and enabling farmers
Irrigation is one of the
processes involving human-intensive methods of agriculture. Machines trained on
historical weather patterns, soil quality and crop types to grow will automate
irrigation and increase overall yield production. With nearly 65-75% of the
world's freshwater used in irrigation, automation will help farmers handle
their water problems better.
Restraint
High
cost & lack of standardization
High device and service
costs are a major factor hampering global artificial intelligence (AI)
development in the agricultural industry. Furthermore, the lack of
standardization limits market growth as data collection requirements are
lacking and the lack of data sharing is strong, and machine learning and
artificial intelligence and advanced algorithm design have progressed so
rapidly, but the collection of well-tagged, usable agricultural data is far
behind.
Global
AI in Agriculture Market: Offering
Based on the global
Agriculture market, AI being offered fragmented into hardware, software &
services. During the forecast period, the Hardware segment market is expected
to rise at the highest CAGR. The growing demand for processors and data storage
devices for farm operations is the significant factor that is likely to
contribute to the hardware market's high growth rate in the coming years.
Followed by the hardware industry, the software provides significantly to the
global market growth rate. The software category is driven primarily by the
convergence of mobile devices with farming techniques, increased use of artificial
intelligence tools to boost farm productivity and increased demand for data
management systems in real-time.
Global
AI in Agriculture Market: Technology
Global
AI in Agriculture Market: Application
The market is segmented,
based on application, into agricultural robots, precision farming, drone
analytics, livestock monitoring, and others, including smart greenhouse
management, soil management, and fishery management. The segment of precision
farming is expected to account for a substantial market share during the
forecast period. It helps farmers minimize costs and effectively optimize
resources. Precision agriculture uses AI to capture, view and analyze digital
data. For example, GPS-equipped harvesters deploy artificial intelligence to
track harvest yields for field variability analysis, such as variations in
water, soil composition or fungus, to generate geo-referenced data this is due
to precision farming, which is gaining popularity among farmers as a result of
the growing need for optimum yield with limited resources available, resulting
in a cost-effective approach. In addition, the rapid use of IoT in the
agriculture sector leads to the growth of the precision agricultural market.
Global
AI in Agriculture Market: Regional Insights
In the agricultural market,
North America is assessed as the dominant locale in worldwide AI. Market growth
is due to the high variety of trend-setting products and agricultural goods. In
addition, selecting the prescient review and remote monitoring innovation in
agriculture also contributes substantially to the growth of the industry.
Besides, higher technological knowledge promotes the development of the AI
market in agriculture. Moving on from North America, Asia-Pacific expected a
significant growth during the 2020-2026 forecast period. The significant
factors contributing to the growth of AI in APAC's agricultural sector include
increasing precision farming practices to increase crop yields, drone analytics
services, and growing farm robots ' adoption. Farmers in countries such as
Australia, China, Japan, and India are rapidly embracing technology for machine
learning, deep learning, computer vision and predictive analytics.
Competitive Landscape
Artificial intelligence in Agriculture market is fragmented into large-sized companies, mid-sized & small-sized companies, and many start-ups that provide artificial intelligence in Agriculture industry. However, the companies that hold the majority share of artificial intelligence in Agriculture market are IBM Corporation, Microsoft Corporation, Bayer AG, Deere & Company, A.A.A. Taranis Visual Ltd, AgEagle Aerial Systems Inc., AGCO Corporation, Raven Industries, Ag Leader Technology, Trimble Inc., Google LLC, Gamaya SA, Granular Inc., PrecisionHawk, SAP and Other Prominent Players.
The
objective of the Study:
·
To analyze and forecast the global market
size of the AI in agriculture.
·
Analyzing careful market segmentation and
estimating value-based market size through region-based segmentation.
· The global AI market for agriculture is
divided into five regions: North America, Europe, Asia-Pacific, Middle East,
South America, and their leading countries.
· To outline, categorize and forecast the
global AI in the agricultural market based on the range of products,
technology, and applications linked to the region.
· To examine competitive developments in the
global AI market, such as technological advancement, services, and regulatory
framework.
·
To emphasize the impact study of market
dynamics variables such as users, constraints, opportunities, and challenges.
· Profiling key players strategically and
analyzing their market shares comprehensively, together with detailing the
competitive environment for market leaders.
Scope of the Report
|
Attribute |
Details |
|
Years
Considered |
Historical data – 2016-2019 Base Year – 2019 Forecast – 2020 – 2026 |
|
Facts Covered |
Revenue in USD Million/Billion |
|
Market Coverage |
U.S, Canada, Germany, UK, France, Italy,
Spain, Brazil, Mexico, Argentina, Japan, South Korea, China, India, UAE,
South Africa, Saudi Arabia |
|
Product/Service Segmentation |
By Offering, By
Technology, By Application and region |
|
Key Players |
IBM Corporation, Microsoft Corporation, Bayer AG, Deere &
Company, A.A.A. Taranis Visual Ltd, AgEagle Aerial Systems Inc., AGCO
Corporation, Raven Industries, Ag Leader Technology, Trimble Inc., Google
LLC, Gamaya SA, Granular Inc., PrecisionHawk, SAP and Other Prominent Players |
By Offering
·
Hardware
o
Processor
o
Storage
Device
o
Network
·
Software
o
AI
Solutions
o
AI
Platform
·
Services
o
Deployment
& Integration
o
Support
& Maintenance
By Technology
·
Machine
Learning
·
Computer
Vision
·
Predictive
Analytics
By Application
·
Precision
Farming
·
Yield Monitoring
o
Field Mapping
o
Crop Scouting
o
Weather Tracking and Forecasting
o
Irrigation Management
·
Livestock
Monitoring
·
Drone
Analytics
·
Agriculture
Robots
·
Other
Applications (Smart Greenhouse Application, Soil Management etc.)
By Region:
·
North America
·
Europe
·
Asia Pacific
·
Latin America
·
Middle East & Africa
Recent
Development
· June 2019 - At the 3rd AI Good Global Summit in Geneva, XAG, a Chinese company, presented its innovative solutions for integrating drones with AI and IoT technologies to achieve precision farming and introduce revolutionary changes to the food system. XAG drives AI-powered intelligent devices such as drones and sensors to develop digital farming infrastructure in rural areas and enables precision agriculture wherever it is required, which, for example, targets precisely pesticides, seeds, fertilizers and water.
· April 2019 - Yara and IBM
Services have joined forces in innovating and selling digital agricultural
technologies that will help boost global food production. Yara and IBM will be
designing digital technologies that enable skilled and smallholder farmers to
improve farming practices in a sustainable manner to increase yields, crop
quality and profits. The collaboration will focus on all aspects of farm
optimization and apply AI, machine learning and in-field data to unlock new
insights for farmers, especially in the field of weather data, where weather
companies will provide real-time actionable recommendations for hyperlocal
weather forecasts tailored to the specific needs of individual fields / crops.
Business
Questions Answer by the Report
· How will the market drivers, restraints, and
opportunities affect the market dynamics?
· What will be the market size in terms of
value and volume and market statistics with
a detailed classification?
· Which segment dominates the market or
region, and one will be the fastest-growing, and why?
· A comprehensive survey of the competitive
landscape and the market participant players
· Analysis of strategy adopted by the key
player and their impact on other players.
Customization
Scope for the Client
Client satisfaction is our first and last priority, and that’s why
BlueWeave Consulting offers customization according to Company’s specific
needs. The following customization options are available for the report:
Additional
Company Information
· With five
additional company detail analysis
· Additional
country analysis
· Detailed segment analysis
1. Research Framework
1.1. Research
Objective
1.2. Product
Overview
1.3. Market
Segmentation
2. Research Methodology
2.1. Qualitative
Research
2.1.1.
Primary & Secondary Sources
2.2. Quantitative
Research
2.2.1.
Primary & Secondary Sources
2.3. Breakdown
of Primary Research Respondents, By Region
2.3.1.
Secondary Research
2.3.2.
Primary Research
2.4. Breakdown
of Primary Research Respondents
2.5. Market
Size Estimation
2.6. Assumption
for The Study
2.7. Market
Breakdown & Data Triangulation
3. Executive Summary
4. Global AI in Agriculture Insights
4.1. Industry
Value Chain Analysis
4.2. DROC
Analysis
4.2.1.
Growth Drivers
4.2.2.
Restraints
4.2.3.
Opportunities
4.2.4.
Challenges
4.3. Technological
Landscape
4.4. Regulatory
Framework
4.5. Company
Market Share Analysis,2019
4.6. Porter’s
Five forces analysis
4.6.1.
Bargaining Power of Suppliers
4.6.2.
Bargaining Power of Buyers
4.6.3.
Threat of New Entrants
4.6.4.
Threat of Substitutes
4.6.5.
Intensity of Rivalry
4.7. Strategic
Outlook
5. Global AI in Agriculture Market Overview
5.1. Market
Estimates & Forecast by Value, 2016-2026
5.1.1.
By Value (USD)
5.2. Market
Share & Forecast
5.2.1.
By Offering
5.2.1.1.
Hardware
5.2.1.1.1.
Processor
5.2.1.1.2.
Storage Device
5.2.1.1.3.
Network
5.2.1.2.
Software
5.2.1.2.1.
AI Solutions
5.2.1.2.2.
AI Platform
5.2.1.3.
Services
5.2.1.3.1.
Deployment & Integration
5.2.1.3.2.
Support & Maintenance
5.2.2.
By Technology
5.2.2.1.
Machine Learning
5.2.2.2.
Computer Vision
5.2.2.3.
Predictive Analytics
5.2.3.
By Application
5.2.3.1.
Precision Farming
5.2.3.2.
Yield Monitoring
5.2.3.2.1.
Field Mapping
5.2.3.2.2.
Crop Scouting
5.2.3.2.3.
Weather Tracking and Forecasting
5.2.3.2.4.
Irrigation Management
5.2.3.3.
Livestock Monitoring
5.2.3.4.
Drone Analytics
5.2.3.5.
Agriculture Robots
5.2.3.6.
Other Applications (Smart Greenhouse
Application, Soil Management etc.)
5.2.4.
By Region
5.2.4.1.
North America
5.2.4.2.
Europe
5.2.4.3.
Asia Pacific
5.2.4.4.
Latin America
5.2.4.5.
Middle East & Africa
6. North America AI in Agriculture Market
6.1. Market
Estimates & Forecast by Value, 2016-2026
6.1.1.
By Value (USD)
6.2. Market
Share & Forecast
6.2.1.
By Offering
6.2.2.
By Technology
6.2.3.
By Application
6.2.4.
By Country
6.2.4.1.
U.S
6.2.4.2.
Canada
7. Europe AI in Agriculture Market
7.1. Market
Estimates & Forecast by Value, 2016-2026
7.1.1.
By Value (USD)
7.2. Market
Share & Forecast
7.2.1.
By Offering
7.2.2.
By Technology
7.2.3.
By Application
7.2.4.
By Country
7.2.4.1.
Germany
7.2.4.2.
U.K
7.2.4.3.
France
7.2.4.4.
Italy
7.2.4.5.
Rest of Europe
8. Asia Pacific AI in Agriculture Market
8.1. Market
Estimates & Forecast by Value, 2016-2026
8.1.1.
By Value (USD)
8.2. Market
Share & Forecast
8.2.1.
By Offering
8.2.2.
By Technology
8.2.3.
By Application
8.2.4.
By Country
8.2.4.1.
China
8.2.4.2.
India
8.2.4.3.
Japan
8.2.4.4.
South Korea
8.2.4.5.
Rest of APAC
9.
Latin America AI in Agriculture Market
9.1. Market
Estimates & Forecast by Value, 2016-2026
9.1.1.
By Value (USD)
9.2. Market
Share & Forecast
9.2.1.
By Offering
9.2.2.
By Technology
9.2.3.
By Application
9.2.4.
By Country
9.2.4.1.
Brazil
9.2.4.2.
Mexico
9.2.4.3.
Argentina
9.2.4.4.
Rest of Latin America
10.Middle East & Africa AI in
Agriculture Market
10.1.
Market Estimates & Forecast by Value,
2016-2026
10.1.1.
By Value (USD)
10.2.
Market Share & Forecast
10.2.1.
By Offering
10.2.2.
By Technology
10.2.3.
By Application
10.2.4.
By Country
10.2.4.1.
Saudi Arabia
10.2.4.2.
UAE
10.2.4.3.
South Africa
10.2.4.4.
Rest of MEA
11.Company Profile (Company Overview,
Financial Matrix, Product landscape, Key Personnel, Key Competitors, Contact
Address, and Strategic Outlook) *
11.1.
IBM Corporation
11.2.
Microsoft Corporation
11.3.
Bayer AG
11.4.
Deere & Company
11.5.
A.A.A. Taranis Visual Ltd
11.6.
AgEagle Aerial Systems Inc.
11.7.
AGCO Corporation
11.8.
Raven Industries
11.9.
Ag Leader Technology
11.10.
Trimble Inc.
11.11.
Google LLC
11.12.
Gamaya SA
11.13.
Granular Inc.
11.14.
PrecisionHawk
11.15.
SAP
11.16.
Other Prominent Players
*Financial details in case
of unlisted companies will be available as per data availability.
**The segmentation and the companies are subjected to modifications based on the in-depth secondary for the final deliverable
List
of Figures
Fig: Global AI in
Agriculture Segmentation
Fig: Company Market Share
Analysis, 2019
Fig: Global AI in
Agriculture Market Size, By Value (USD Million), 2016-2026
Fig: Global AI in
Agriculture Market Share, By Offering, By Value, 2016-2026
Fig: Global AI in
Agriculture Market Share, By Technology, By Value, 2016-2026
Fig: Global AI in Agriculture
Market Share, By Region, By Value, 2016-2026
Fig: North America AI in
Agriculture Market Size, By Value (USD Million), 2016-2026
Fig: North America AI in
Agriculture Market Y-o-Y Growth, By Value, 2017-2026
Fig: North America AI in
Agriculture Market Share, By Offering, By Value, 2016-2026
Fig: North America AI in
Agriculture Market Share, By Technology, By Value, 2016-2026
Fig: North America AI in
Agriculture Market Share, By Application, By Value, 2016-2026
Fig: North America AI in
Agriculture Market Share, By Country, By Value, 2016-2026
Fig: Europe AI in
Agriculture Market Size, By Value (USD Million), 2016-2026
Fig: Europe AI in
Agriculture Market Y-o-Y Growth, By Value, 2017-2026
Fig: Europe AI in
Agriculture Market Share, By Offering, By Value, 2016-2026
Fig: Europe AI in
Agriculture Market Share, By Technology, By Value, 2016-2026
Fig: Europe AI in
Agriculture Market Share, By Application, By Value, 2016-2026
Fig: Europe AI in
Agriculture Market Share, By Country, By Value, 2016-2026
Fig: Asia-Pacific AI in
Agriculture Market Size, By Value (USD Million), 2016-2026
Fig: Asia-Pacific AI in
Agriculture Market Y-o-Y Growth, By Value, 2017-2026
Fig: Asia-Pacific AI in
Agriculture Market Share, By Offering, By Value, 2016-2026
Fig: Asia-Pacific AI in
Agriculture Market Share, By Technology, By Value, 2016-2026
Fig: Asia-Pacific AI in
Agriculture Market Share, By Application, By Value, 2016-2026
Fig: Asia-Pacific AI in
Agriculture Market Share, By Country, By Value, 2016-2026
Fig: Latin America AI in
Agriculture Market Size, By Value (USD Million), 2016-2026
Fig: Latin America AI in
Agriculture Market Y-o-Y Growth, By Value, 2017-2026
Fig: Latin America AI in
Agriculture Market Share, By Offering, By Value, 2016-2026
Fig: Latin America AI in
Agriculture Market Share, By Technology, By Value, 2016-2026
Fig: Latin America AI in
Agriculture Market Share, By Application, By Value, 2016-2026
Fig: Latin America AI in
Agriculture Market Share, By Country, By Value, 2016-2026
Fig: Middle-East &
Africa AI in Agriculture Market Size, By Value (USD Million), 2016-2026
Fig: Middle-East &
Africa AI in Agriculture Market Y-o-Y Growth, By Value, 2017-2026
Fig: Middle-East &
Africa AI in Agriculture Market Share, By Offering, By Value, 2016-2026
Fig: Middle-East & Africa
AI in Agriculture Market Share, By Technology, By Value, 2016-2026
Fig: Middle-East &
Africa AI in Agriculture Market Share, By Application, By Value, 2016-2026
Fig: Middle East &
Africa AI in Agriculture Market Share, By Country, By Value, 2016-2026
List
of Tables:
Table: Global AI in
Agriculture Market Size, By Offering, By Value, 2016-2026
Table: Global AI in
Agriculture Market Size, By Technology, By Value, 2016-2026
Table: Global AI in
Agriculture Market Size, By Application, By Value, 2016-2026
Table: Global AI in
Agriculture Market Size, By Region, By Value, 2016-2026
Table: North America AI in
Agriculture Market Size, By Offering, By Value, 2016-2026
Table: North America AI in
Agriculture Market Size, By Technology, By Value, 2016-2026
Table: North America l AI in
Agriculture Market Size, By Application, By Value, 2016-2026
Table: North America AI in
Agriculture Market Size, By Country, By Value, 2016-2026
Table: Europe AI in
Agriculture Market Size, By Offering, By Value, 2016-2026
Table: Europe AI in
Agriculture Market Size, By Technology, By Value, 2016-2026
Table: Europe AI in
Agriculture Market Size, By Application, By Value, 2016-2026
Table: Europe AI in
Agriculture Market Size, By Country, By Value, 2016-2026
Table: Asia-Pacific AI in
Agriculture Market Size, By Offering, By Value, 2016-2026
Table: Asia-Pacific AI in
Agriculture Market Size, By Technology, By Value, 2016-2026
Table: Asia-Pacific AI in
Agriculture Market Size, By Application, By Value, 2016-2026
Table: Asia-Pacific AI in
Agriculture Market Size, By Country, By Value, 2016-2026
Table: Latin America AI in
Agriculture Market Size, By Offering, By Value, 2016-2026
Table: Latin America AI in
Agriculture Market Size, By Technology, By Value, 2016-2026
Table: Latin America AI in
Agriculture Market Size, By Application, By Value, 2016-2026
Table: Latin America AI in
Agriculture Market Size, By Country, By Value, 2016-2026
Table: Middle-East &
Africa AI in Agriculture Market Size, By Offering, By Value, 2016-2026
Table: Middle-East &
Africa AI in Agriculture Market Size, By Technology, By Value, 2016-2026
Table: Middle-East &
Africa AI in Agriculture Market Size, By Application, By Value, 2016-2026
Table: Middle East &
Africa AI in Agriculture Market Size, By Country, By Value, 2016-2026
Table: IBM Corporation Financial Analysis
Table: Microsoft Corporation Financial Analysis
Table: Bayer AG Financial Analysis
Table: Deere & Company Financial Analysis
Table: A.A.A. Taranis Visual Ltd Financial Analysis
Table: AgEagle Aerial Systems Inc Financial Analysis
Table: AGCO Corporation Financial Analysis
Table: Raven Industries Financial Analysis
Table: Ag Leader Technology Financial Analysis
Table: Trimble Inc Financial Analysis
Table: Google LLC Financial Analysis
Table: Gamaya SA Financial Analysis
Table: Granular Inc Financial Analysis
Table: PrecisionHawk Financial Analysis
Table: SAP Financial Analysis
Market Segmentation
To request a free sample copy of this report, please complete the form below.
We value your investment and offer free customization with every report to fulfil your exact research needs.
RELATED REPORTS
WHY CHOOSE US
-
24/7 Research support
Get your queries resolved from an industry expert. Request for a free product review before report purchase.
-
Coustom Research Service
Ask the Analyst to customize an exclusive study to serve your research needs
-
Quality & Accuracy
Ask the Analyst to customize an exclusive study to serve your research needs
-
Data Visualization
As the business world is changing dynamically every day. We need to stay pin point in relation to data management and optimum data utilization
-
Information security
We never share your personal and confidential information. Your personal information is safe and secure with us.