
Digital Farming Market
Digital Farming Market Forecasts to 2030 - Global Analysis By Product (Drones/Robots/Unmanned Aerial Vehicles, Agricultural Equipment-s and Other Products), Technology (IoT, Blockchain, AI/ML/NLP, Big Data & Analytics and Other Technologies), Infrastructure, Application and by Geography

Years Covered |
2021-2030 |
Estimated Year Value (2023) |
US $24.91 BN |
Projected Year Value (2030) |
US $71.48 BN |
CAGR (2023 - 2030) |
16.3% |
Regions Covered |
North America, Europe, Asia Pacific, South America, and Middle East & Africa |
Countries Covered |
US, Canada, Mexico, Germany, UK, Italy, France, Spain, Japan, China, India, Australia, New Zealand, South Korea, Rest of Asia Pacific, South America, Argentina, Brazil, Chile, Middle East & Africa, Saudi Arabia, UAE, Qatar, and South Africa |
Largest Market |
Middle East & Africa |
Highest Growing Market |
Europe |
According to Stratistics MRC, the Global Digital Farming Market is accounted for $24.91 billion in 2023 and is expected to reach $71.48 billion by 2030 growing at a CAGR of 16.3% during the forecast period. Digital farming is the use of technologies, services, and products to gather and analyze data and offer farmers the best guidance on managing their land, water, and nutrition. By supporting farmers with the precise and timely application of their crops, the solution contributes to the advancement of agricultural solutions as a whole. It will offer the optimal fertilization program for certain fields, enabling them to choose how much fertilizer to apply and adjust for variations in various fields' regions.
According to a new UN assessment, the world’s current population of 7.6 Billion people will grow to 8.6 Billion in 2030, 9.8 Billion in 2050, and 11.2 Billion in 2100.
Market Dynamics:
Driver:
Rising demand in usage of innovative technologies
The rising need for food brought on by population growth, the increased usage of VRT (variable rate technology), and the growing use of remote sensing and guiding technologies by farmers around the world have all contributed to the significant growth of the global digital farming market in recent years. Furthermore, the use of innovative agricultural techniques has resulted in substantial cost savings, which is anticipated to fuel demand in the global digital farming market throughout the anticipated timeframe.
Restraint:
High cost
Automated agricultural equipment is substantially more expensive than conventional farming equipment. Examples include automated harvesters, weeding robots, tillers, and irrigation systems supported by robots. Moreover, the cost of maintaining modern vehicles further limits the use of smart digital farming technologies by small farmers. Therefore, the upkeep costs for the sensors, software, hardware, and cameras in these cars may slow market expansion.
Opportunity:
Technological advancements
Technologies like machine learning and artificial intelligence are being swiftly incorporated into farming equipment or field methods. Additionally, as it increases productivity and aids in learning, understanding, and responding to various situations, cognitive computing is gaining popularity across the industry. Moreover, the agriculture industry is similarly undergoing a digital revolution as a result of new initiatives being introduced by both public and commercial organizations. Internet of things solutions aid in the effective use of natural resources like water, power, and others. Users can monitor crop health and soil moisture using a variety of sensors, including light, humidity, temperature, and others included in Internet of Things (IoT) devices. Thus, computerized farm management systems make it possible to monitor farm operations from any location.
Threat:
Lack of awareness and understanding
The main challenge with digital farming is a lack of knowledge and comprehension of technology. However, understanding the workings of new technology and anticipating how things will change require a creative approach. The principles of digital farming are unknown to many farmers. Hence, lack of knowledge and understanding, as well as the expensive price of cutting-edge machinery and technology, are projected to hinder the global digital farming market throughout the forecast period.
Covid-19 Impact
Due to the state-wide lockdowns, travel restrictions, and suspension of import and export activity caused by the COVID-19 pandemic's impact on migrant and rural labourers’ freedom of movement, the agriculture industry was severely disrupted. Global food output was impeded by the severe labor shortage caused by this circumstance. Since there were constrained shipments and an adverse business environment, the pandemic also decreased sales of agricultural equipment. Sales of intelligent farming equipment were delayed by the disruption in the supply chain, which also had an impact on the industry's distribution networks.
The hardware segment is expected to be the largest during the forecast period
The hardware segment is estimated to hold the largest share, because businesses in the digital farming sector are constantly looking for fresh ways to offer consumers cutting-edge goods and services. The Digital Farming Market is home to a few businesses that also sell farming robots. Therefore, the approachable front-end framework of this infrastructure will boost farmers' productivity and output, and they will be able to take advantage of yield opportunities to eliminate world hunger and deal with challenges with limited arable land everywhere.
The Artificial intelligence/Machine learning/Natural language processing segment is expected to have the highest CAGR during the forecast period
The Artificial intelligence/Machine learning/Natural language processing segment is anticipated to have lucrative growth during the forecast period, due to the demand for integrating technologies like artificial intelligence and machine learning into agricultural machinery is rising as a result of the need for automated and cutting-edge equipment for farming. Moreover, businesses are developing cutting-edge AI-powered solutions to recognize weather patterns, soil health, crop health, weeds, and pests, which enable them to boost market sustainability.
Region with largest share:
Middle East & Africa commanded the largest market share during the extrapolated period owing to the expansion of smart technology and the internet in the area is attributed to the market expansion. There will be plenty of market opportunities due to the numerous efforts made by governments and tech-savvy businesses in Brazil, Argentina, Israel, and the GCC to build a cloud data center and implement emerging technologies like machine learning (ML), artificial intelligence (AI), cloud, big data, and others which boost the market size.
Region with highest CAGR:
Europe is expected to witness profitable growth over the projection period, owing to numerous initiatives were started by the European Union to help farmers use cutting-edge technology in their agricultural endeavours. For instance, The European Union has started a funding initiative called the Life and GAIA Sense project to support intelligent agriculture in the area. Moreover, farmers can get funding through the LIFE GAIA Sense program to place sensors on their properties. These sensors are used to monitor and control a number of factors, such as soil moisture, plant health, and insect control. Hence, such aggressive programs are anticipated to drive market expansion.
Key players in the market
Some of the key players in the Digital Farming Market include Accenture PLC, AgEagle Aerial Systems, AGRO Corporation, Bayer Cropscience Limited, Cisco Systems Inc., CLAAS KGaA mbH, CNH Industrial N.V., Deere & Co., Epicor Software Corporation, Hexagone AB, IBM Corporation, Kubota Corporation, Monsanto Company, Salt Mobile SA, Topcon Corporation, Trimble Navigation Ltd. and Vodafone Group PLC.
Key Developments:
In June 2022, Cropin, a Bangalore-based agriculture technology firm, planned to launch an agriculture cloud (Agcloud). Agcloud contains data about crops and farmers' locations. In addition, it includes applications that help solve agriculture-related problems. The information of farmers is digitized and used to run agriculture programs to select crops.
In May 2022, Trimble launched a dual frequency, GNSS receiver module, the Trimble BD9250. Trimble RTX correction services are supported by the Trimble BD9250. The new module was developed to provide high-accuracy positioning for automated agriculture applications.
Products Covered:
• Drones/Robots/Unmanned Aerial Vehicles
• Agricultural Equipment’s
• Other Products
Technologies Covered:
• Internet of things
• Blockchain
• Artificial intelligence/Machine learning/Natural language processing
• Big Data & Analytics
• Other Technologies
Infrastructures Covered:
• Sensing & Monitoring
• Communication Technology
• Cloud and Data Processing
• Telematics/Positioning
• Other Infrastructures
Applications Covered:
• Weather Forecasting
• Smart Crop Monitoring
• Smart Irrigation Monitoring System
• Yield Monitoring and Mapping
• Soil & Fertilizer Management
• Other Applications
Regions Covered:
• North America
o US
o Canada
o Mexico
• Europe
o Germany
o UK
o Italy
o France
o Spain
o Rest of Europe
• Asia Pacific
o Japan
o China
o India
o Australia
o New Zealand
o South Korea
o Rest of Asia Pacific
• South America
o Argentina
o Brazil
o Chile
o Rest of South America
• Middle East & Africa
o Saudi Arabia
o UAE
o Qatar
o South Africa
o Rest of Middle East & Africa
What our report offers:
- Market share assessments for the regional and country-level segments
- Strategic recommendations for the new entrants
- Covers Market data for the years 2021, 2022, 2023, 2026, and 2030
- Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
- Strategic recommendations in key business segments based on the market estimations
- Competitive landscaping mapping the key common trends
- Company profiling with detailed strategies, financials, and recent developments
- Supply chain trends mapping the latest technological advancements
Free Customization Offerings:
All the customers of this report will be entitled to receive one of the following free customization options:
• Company Profiling
o Comprehensive profiling of additional market players (up to 3)
o SWOT Analysis of key players (up to 3)
• Regional Segmentation
o Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
• Competitive Benchmarking
o Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances
Table of Contents
1 Executive Summary
2 Preface
2.1 Abstract
2.2 Stake Holders
2.3 Research Scope
2.4 Research Methodology
2.4.1 Data Mining
2.4.2 Data Analysis
2.4.3 Data Validation
2.4.4 Research Approach
2.5 Research Sources
2.5.1 Primary Research Sources
2.5.2 Secondary Research Sources
2.5.3 Assumptions
3 Market Trend Analysis
3.1 Introduction
3.2 Drivers
3.3 Restraints
3.4 Opportunities
3.5 Threats
3.6 Product Analysis
3.7 Technology Analysis
3.8 Application Analysis
3.9 Emerging Markets
3.10 Impact of Covid-19
4 Porters Five Force Analysis
4.1 Bargaining power of suppliers
4.2 Bargaining power of buyers
4.3 Threat of substitutes
4.4 Threat of new entrants
4.5 Competitive rivalry
5 Global Digital Farming Market, By Product
5.1 Introduction
5.2 Drones/Robots/Unmanned Aerial Vehicles
5.3 Agricultural Equipment’s
5.4 Other Products
6 Global Digital Farming Market, By Technology
6.1 Introduction
6.2 Internet of things
6.3 Blockchain
6.4 Artificial intelligence/Machine learning/Natural language processing
6.5 Big Data & Analytics
6.6 Other Technologies
7 Global Digital Farming Market, By Infrastructure
7.1 Introduction
7.2 Sensing & Monitoring
7.2.1 Sensors
7.2.2 Cameras
7.3 Communication Technology
7.3.1 Medium Range
7.3.2 Long Range
7.3.3 Short Range
7.4 Cloud and Data Processing
7.5 Telematics/Positioning
7.5.1 Geographic Information System
7.5.2 Global Positioning System/Global Navigation Satellite System
7.6 Other Infrastructures
8 Global Digital Farming Market, By Application
8.1 Introduction
8.2 Weather Forecasting
8.3 Smart Crop Monitoring
8.4 Smart Irrigation Monitoring System
8.5 Yield Monitoring and Mapping
8.6 Soil & Fertilizer Management
8.7 Other Applications
9 Global Digital Farming Market, By Geography
9.1 Introduction
9.2 North America
9.2.1 US
9.2.2 Canada
9.2.3 Mexico
9.3 Europe
9.3.1 Germany
9.3.2 UK
9.3.3 Italy
9.3.4 France
9.3.5 Spain
9.3.6 Rest of Europe
9.4 Asia Pacific
9.4.1 Japan
9.4.2 China
9.4.3 India
9.4.4 Australia
9.4.5 New Zealand
9.4.6 South Korea
9.4.7 Rest of Asia Pacific
9.5 South America
9.5.1 Argentina
9.5.2 Brazil
9.5.3 Chile
9.5.4 Rest of South America
9.6 Middle East & Africa
9.6.1 Saudi Arabia
9.6.2 UAE
9.6.3 Qatar
9.6.4 South Africa
9.6.5 Rest of Middle East & Africa
10 Key Developments
10.1 Agreements, Partnerships, Collaborations and Joint Ventures
10.2 Acquisitions & Mergers
10.3 New Product Launch
10.4 Expansions
10.5 Other Key Strategies
11 Company Profiling
11.1 Accenture PLC
11.2 AgEagle Aerial Systems
11.3 AGRO Corporation
11.4 Bayer Cropscience Limited
11.5 Cisco Systems Inc.
11.6 CLAAS KGaA mbH
11.7 CNH Industrial N.V.
11.8 Deere & Co.
11.9 Epicor Software Corporation
11.10 Hexagone AB
11.11 IBM Corporation
11.12 Kubota Corporation
11.13 Monsanto Company
11.14 Salt Mobile SA
11.15 Topcon Corporation
11.16 Trimble Navigation Ltd.
11.17 Vodafone Group PLC
List of Tables
1 Global Digital Farming Market Outlook, By Region (2021-2030) ($MN)
2 Global Digital Farming Market Outlook, By Product (2021-2030) ($MN)
3 Global Digital Farming Market Outlook, By Drones/Robots/Unmanned Aerial Vehicles (2021-2030) ($MN)
4 Global Digital Farming Market Outlook, By Agricultural Equipment’s (2021-2030) ($MN)
5 Global Digital Farming Market Outlook, By Other Products (2021-2030) ($MN)
6 Global Digital Farming Market Outlook, By Technology (2021-2030) ($MN)
7 Global Digital Farming Market Outlook, By Internet of things (2021-2030) ($MN)
8 Global Digital Farming Market Outlook, By Blockchain (2021-2030) ($MN)
9 Global Digital Farming Market Outlook, By Artificial intelligence/Machine learning/Natural language processing (2021-2030) ($MN)
10 Global Digital Farming Market Outlook, By Big Data & Analytics (2021-2030) ($MN)
11 Global Digital Farming Market Outlook, By Other Technologies (2021-2030) ($MN)
12 Global Digital Farming Market Outlook, By Infrastructure (2021-2030) ($MN)
13 Global Digital Farming Market Outlook, By Sensing & Monitoring (2021-2030) ($MN)
14 Global Digital Farming Market Outlook, By Sensors (2021-2030) ($MN)
15 Global Digital Farming Market Outlook, By Cameras (2021-2030) ($MN)
16 Global Digital Farming Market Outlook, By Communication Technology (2021-2030) ($MN)
17 Global Digital Farming Market Outlook, By Medium Range (2021-2030) ($MN)
18 Global Digital Farming Market Outlook, By Long Range (2021-2030) ($MN)
19 Global Digital Farming Market Outlook, By Short Range (2021-2030) ($MN)
20 Global Digital Farming Market Outlook, By Cloud and Data Processing (2021-2030) ($MN)
21 Global Digital Farming Market Outlook, By Telematics/Positioning (2021-2030) ($MN)
22 Global Digital Farming Market Outlook, By Geographic Information System (2021-2030) ($MN)
23 Global Digital Farming Market Outlook, By Global Positioning System/Global Navigation Satellite System (2021-2030) ($MN)
24 Global Digital Farming Market Outlook, By Other Infrastructures (2021-2030) ($MN)
25 Global Digital Farming Market Outlook, By Application (2021-2030) ($MN)
26 Global Digital Farming Market Outlook, By Weather Forecasting (2021-2030) ($MN)
27 Global Digital Farming Market Outlook, By Smart Crop Monitoring (2021-2030) ($MN)
28 Global Digital Farming Market Outlook, By Smart Irrigation Monitoring System (2021-2030) ($MN)
29 Global Digital Farming Market Outlook, By Yield Monitoring and Mapping (2021-2030) ($MN)
30 Global Digital Farming Market Outlook, By Soil & Fertilizer Management (2021-2030) ($MN)
31 Global Digital Farming Market Outlook, By Other Applications (2021-2030) ($MN)
Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.
List of Figures
List of Figures
Figure 1 Global Digital Farming Market Outlook (2021-2030) ($MN)
Figure 2 North America Digital Farming Market Outlook (2021-2030) ($MN)
Figure 3 US Digital Farming Market Outlook (2021-2030) ($MN)
Figure 4 Canada Digital Farming Market Outlook (2021-2030) ($MN)
Figure 5 Mexico Digital Farming Market Outlook (2021-2030) ($MN)
Figure 6 Europe Digital Farming Market Outlook (2021-2030) ($MN)
Figure 7 Germany Digital Farming Market Outlook (2021-2030) ($MN)
Figure 8 UK Digital Farming Market Outlook (2021-2030) ($MN)
Figure 9 Italy Digital Farming Market Outlook (2021-2030) ($MN)
Figure 10 France Digital Farming Market Outlook (2021-2030) ($MN)
Figure 11 Spain Digital Farming Market Outlook (2021-2030) ($MN)
Figure 12 Rest of Europe Digital Farming Market Outlook (2021-2030) ($MN)
Figure 13 Asia Pacific Digital Farming Market Outlook (2021-2030) ($MN)
Figure 14 Japan Digital Farming Market Outlook (2021-2030) ($MN)
Figure 15 China Digital Farming Market Outlook (2021-2030) ($MN)
Figure 16 India Digital Farming Market Outlook (2021-2030) ($MN)
Figure 17 Australia Digital Farming Market Outlook (2021-2030) ($MN)
Figure 18 New Zealand Digital Farming Market Outlook (2021-2030) ($MN)
Figure 19 South Korea Digital Farming Market Outlook (2021-2030) ($MN)
Figure 20 Rest of Asia Pacific Digital Farming Market Outlook (2021-2030) ($MN)
Figure 21 South America Digital Farming Market Outlook (2021-2030) ($MN)
Figure 22 Argentina Digital Farming Market Outlook (2021-2030) ($MN)
Figure 23 Brazil Digital Farming Market Outlook (2021-2030) ($MN)
Figure 24 Chile Digital Farming Market Outlook (2021-2030) ($MN)
Figure 25 Rest of South America Digital Farming Market Outlook (2021-2030) ($MN)
Figure 26 Middle East & Africa Digital Farming Market Outlook (2021-2030) ($MN)
Figure 27 Saudi Arabia Digital Farming Market Outlook (2021-2030) ($MN)
Figure 28 UAE Digital Farming Market Outlook (2021-2030) ($MN)
Figure 29 Qatar Digital Farming Market Outlook (2021-2030) ($MN)
Figure 30 South Africa Digital Farming Market Outlook (2021-2030) ($MN)
Figure 31 Rest of Middle East & Africa Digital Farming Market Outlook (2021-2030) ($MN)
RESEARCH METHODOLOGY

We at ‘Stratistics’ opt for an extensive research approach which involves data mining, data validation, and data analysis. The various research sources include in-house repository, secondary research, competitor’s sources, social media research, client internal data, and primary research.
Our team of analysts prefers the most reliable and authenticated data sources in order to perform the comprehensive literature search. With access to most of the authenticated data bases our team highly considers the best mix of information through various sources to obtain extensive and accurate analysis.
Each report takes an average time of a month and a team of 4 industry analysts. The time may vary depending on the scope and data availability of the desired market report. The various parameters used in the market assessment are standardized in order to enhance the data accuracy.
Data Mining
The data is collected from several authenticated, reliable, paid and unpaid sources and is filtered depending on the scope & objective of the research. Our reports repository acts as an added advantage in this procedure. Data gathering from the raw material suppliers, distributors and the manufacturers is performed on a regular basis, this helps in the comprehensive understanding of the products value chain. Apart from the above mentioned sources the data is also collected from the industry consultants to ensure the objective of the study is in the right direction.
Market trends such as technological advancements, regulatory affairs, market dynamics (Drivers, Restraints, Opportunities and Challenges) are obtained from scientific journals, market related national & international associations and organizations.
Data Analysis
From the data that is collected depending on the scope & objective of the research the data is subjected for the analysis. The critical steps that we follow for the data analysis include:
- Product Lifecycle Analysis
- Competitor analysis
- Risk analysis
- Porters Analysis
- PESTEL Analysis
- SWOT Analysis
The data engineering is performed by the core industry experts considering both the Marketing Mix Modeling and the Demand Forecasting. The marketing mix modeling makes use of multiple-regression techniques to predict the optimal mix of marketing variables. Regression factor is based on a number of variables and how they relate to an outcome such as sales or profits.
Data Validation
The data validation is performed by the exhaustive primary research from the expert interviews. This includes telephonic interviews, focus groups, face to face interviews, and questionnaires to validate our research from all aspects. The industry experts we approach come from the leading firms, involved in the supply chain ranging from the suppliers, distributors to the manufacturers and consumers so as to ensure an unbiased analysis.
We are in touch with more than 15,000 industry experts with the right mix of consultants, CEO's, presidents, vice presidents, managers, experts from both supply side and demand side, executives and so on.
The data validation involves the primary research from the industry experts belonging to:
- Leading Companies
- Suppliers & Distributors
- Manufacturers
- Consumers
- Industry/Strategic Consultants
Apart from the data validation the primary research also helps in performing the fill gap research, i.e. providing solutions for the unmet needs of the research which helps in enhancing the reports quality.
For more details about research methodology, kindly write to us at info@strategymrc.com
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