|Study Period:||2016 - 2026|
|Fastest Growing Market:||Asia Pacific|
|Largest Market:||North America|
Need a report that reflects how COVID-19 has impacted this market and its growth?
The global artificial intelligence in agriculture market is projected to register a CAGR of 4.2% during the forecast period (2021-2026).
Before COVID-19, the adoption of AI in agriculture was already rising, but during the pandemic, the market has witnessed further growth. There is an increase in the implementation of AI through a variety of sensors, drones, and SaaS. These innovative technologies have helped farmers save their crops and recover from the loss they incurred due to the pandemic-related lockdowns. Hence, COVID-19 has had a positive impact on the market indirectly.
Machine learning techniques can maximize crop yields, and this is driving the market. Species selection is a tedious search for specific genes to determine water and nutrient usage effectiveness, adaptability to climate change, disease resistance, nutrient content, and taste. Machine learning, in particular deep learning algorithms, takes decades of field data to analyze crop performance in various climates. Based on this data, one can build a probability model to predict which genes will most likely contribute toward a beneficial trait to a plant. Moreover, an increase in the adoption of cattle face recognition technology is driving the market. By applying advanced metrics, including cattle facial recognition programs and image classification incorporated with body condition scores and feeding patterns, dairy farms are now able to monitor all behavioral aspects in a group of cattle individually. However, the lack of standardization in data collection and a lack of data sharing are restraining the market growth. Machine learning, artificial intelligence, and advanced algorithm designs have advanced fast, but the collection of well-tagged, meaningful agricultural data is lagging. This might hold back the market’s growth during the forecast period.
Scope of the Report
Artificial intelligence technology supports the agriculture sector to boost productivity and efficiency by reducing hostile impacts on the environment. The global artificial intelligence in agriculture market is segmented by application (weather tracking, precision farming, and drone analytics), deployment (cloud, on-premise, and hybrid), and geography (North America, Europe, Asia-Pacific, South America, and Africa).
Key Market Trends
Labor Shortage and Increasing Costs of Labor to Drive the Artificial Intelligence Market
A massive workforce decline is being observed worldwide for many reasons. A lack of skilled labor, aging farmers, and younger generations finding farming an unattractive profession contribute to this decline, thus encouraging trends for automated farming operations. According to the NSS and PLFS (2018-19) report, the agriculture sector’s contribution to employment declined from 81.0% in 1983 to 58.0% in 2018; according to the International Labor Organization(ILO), the percentage of agricultural laborers in the workforce declined from 81.0% to 48.2% in developing countries in 2018. On a similar note, developed countries are not an exception in this declining trend. Asia-Pacific, where agriculture occupies a significant part of the economy, is witnessing a massive decline in the workforce, nearly about a decline of 9.0% between 2015 and 2017. In Japan, the number of people working in farms witnessed a steep fall to 1.7 million in 2015, a 15% decline from the previous year. The European agricultural sector has also faced an enormous decline in the workforce, nearly accounting for 12.8% for the corresponding period. The trend of decline in the agricultural workforce is encouraging governments and private organizations to focus on automating operations by adopting artificial intelligence technologies in the agricultural sector. Owing to the above factors, the market for artificial intelligence in the agricultural sector is likely to boom in the years to come.
To understand key trends, Download Sample Report
China's Technological Innovations to accelerate the Agriculture Sector
The technological innovations in the Chinese market are also accelerating the growth and transforming the global artificial intelligence market in the agricultural sector. In recent years, technologies such as AI have been aggressively deployed to accelerate the modernization of Chinese agriculture. These technologies are being applied mainly in planting, animal husbandry, and agricultural services. For instance, McFly's Intelligent agricultural monitoring drone, GAGO's large scale application of AI technology in crop production and livestock farming, and UniStrong's "Huinong" Beidou navigation agricultural automatic driving system are a few recent innovations prevailing in the Chinese AI sector. Additionally, some of the technological giants have also begun to make deployment in the agricultural sector. For instance, in 2018, JD.com's "Jing Dong Farm" made its debut; similarly, in June 2018, Alibaba's Et agricultural brain was launched. Thus, increasing innovations in the Chinese AI sector are likely to further boost the adoption of AI in the agricultural sector in the coming future.
To understand geography trends, Download Sample Report
The AI in agriculture market is fragmented, as a number of players are supplying the same product at a lower cost, which makes market competition stiff. Also, technological advancements by players and the presence of local and regional players pose a major threat in the price-sensitive market. Key players are Microsoft Corp., IBM Corp. (NITI Aayog), Agribotix LLC, etc.
In July 2020, Prospera Technologies and Bayer partnered to help improve the output at greenhouses by using big data and machine learning.
In November 2017, Microsoft took AI in agriculture a step further by collaborating with United Phosphorous (UPL), for the Pest Risk Prediction API using AI and machine learning to indicate in advance the risk of pest attack.
Table of Contents
1.1 Study Assumptions and Market Definition
1.2 Scope of the Study
2. RESEARCH METHODOLOGY
3. EXECUTIVE SUMMARY
4. MARKET DYNAMICS
4.1 Market Overview
4.2 Market Drivers
4.3 Market Restraints
4.4 Porter's Five Forces Analysis
4.4.1 Threat of New Entrants
4.4.2 Bargaining Power of Buyers/Consumers
4.4.3 Bargaining Power of Suppliers
4.4.4 Threat of Substitute Products
4.4.5 Intensity of Competitive Rivalry
5. MARKET SEGMENTATION
5.1.1 Weather Tracking
5.1.2 Precision Farming
5.1.3 Drone Analytics
5.3.1 North America
22.214.171.124 United States
126.96.36.199 Rest of North America
188.8.131.52 United Kingdom
184.108.40.206 Rest of Europe
220.127.116.11 Rest of Asia-Pacific
5.3.4 South America
18.104.22.168 Rest of South America
22.214.171.124 South Africa
126.96.36.199 Rest of Africa
6. COMPETITIVE LANDSCAPE
6.1 Most Adopted Strategies
6.2 Market Share Analysis
6.3 Company Profiles
6.3.1 Microsoft Corporation
6.3.2 IBM Corporation
6.3.3 Granular, Inc.
6.3.4 aWhere, Inc.
6.3.5 Prospera Technologies Ltd.
6.3.6 Gamaya SA
6.3.8 PrecisionHawk Inc.
6.3.9 Cainthus Corp.
6.3.10 Tule Technologies Inc.
7. MARKET OPPORTUNITIES AND FUTURE TRENDS
8. AN ASSESSMENT OF COVID-19 IMPACT ON THE MARKET
You can also purchase parts of this report. Do you want to check out a section wise price list?
Frequently Asked Questions
What is the study period of this market?
The Artificial Intelligence in Agriculture Market market is studied from 2016 - 2026.
What is the growth rate of Artificial Intelligence in Agriculture Market?
The Artificial Intelligence in Agriculture Market is growing at a CAGR of 4.2% over the next 5 years.
Which region has highest growth rate in Artificial Intelligence in Agriculture Market?
Asia Pacific is growing at the highest CAGR over 2021- 2026.
Which region has largest share in Artificial Intelligence in Agriculture Market?
North America holds highest share in 2020.
Who are the key players in Artificial Intelligence in Agriculture Market?
Microsoft Corporation, IBM corporation, Granular, Inc., aWhere, Inc., Prospera Technologies Ltd. are the major companies operating in Artificial Intelligence in Agriculture Market.