Analysts at GMI Research estimates that the AI in agriculture market was worth USD 1.2 billion in 2021, and forecast to touch USD 6.5 billion in 2029, growing at a significant higher CAGR 23.1% from 2021-2029..

To have the edge over the competition by knowing the market dynamics and current trends of “Artificial Intelligence in Agriculture Market,” request for Sample Report here

Key Drivers

The growing demand for agriculture production driven by the increasing population rate, rising implementation of information management systems and advanced technologies, such as machine learning and deep learning techniques, for improving crop productivity, and increasing number of government initiatives are the major factors that are driving the growth of the global AI in the agriculture market. AI-enabled applications help to control pests, improves the quality of crops, monitor the soil, and enhances agriculture-associated tasks in the complete food supply chain. The increasing inclination towards technologies like satellite remote sensing from traditional farming approaches to supervise crop health will bolster the market growth. Moreover, intensified investments in precision farming and growing adoption of AI technology among farmers to record temperature, soil composition, and crop humidity, will augment the overall market outlook. For example, precision farming startup CropIn, received a funding of $20 million from investors like ABC World Asia to drive the growth.

In addition to this, the accelerated adoption of Internet of Things and AI technologies such as machine learning, computer vision, predictive analytics, and deep learning to asses soil moisture, temperature, weather conditions, plant health and other functions, are further boosting the growth of AI in agriculture market. Furthermore, the growing adoption of automation in agriculture to allocate resources like fertilizers and water, identify the optimal date for crop sowing, and identify weeds, thereby fueling the demand for artificial intelligence solutions. Moreover, AI aids in improving yield quality and reduces the labor cost that is also paving the demand for AI in agriculture. The start-ups in agriculture are widely adopting AI-enabled methodology to boost the efficiency of agricultural production. Applying AI-enabled approaches helps in identifying diseases or climatic changes more quickly and responds smartly. All these factors are drastically driving the growth of the market in the coming years. On the other end of the spectrum, the high cost related to the collection of precise field data is restraining Global AI in Agriculture Market size.

Do you want to know more about the Research process and detailed Methodology, Request Research Methodology of this report

Technology – Segment Analysis

Based on the technology, the computer vision segment is expected to grow at a higher CAGR during the forecast period. Computer vision is involved with the automatic extraction, analysis, and understanding of helpful and meaning data from a single image or a sequence of images. The AI-enabled equipment based on computer vision technology is widely used for detecting a nutrient deficiency or disease in plants and monitors the health of the crops, which is further responsible for driving the market growth. The growing demand for computer vision technology in agriculture applications, such as plant image recognition, followed by the strong demand for analyzing and monitoring the health of the crop, is contributing to the growth of the computer vision technology in AI in the agriculture market. Moreover, the predictive analytics segment is estimated to witness a remarkable growth over the upcoming years, owing to the growing concerns pertaining the impacts of plant diseases on food availability and safety for human and animal consumption.

Offering– Segment Analysis

Based on offering, the software segment is expected to lead the global AI in agriculture market during the forecast period. AI-enabled software improves crop productivity by applying prediction-based analytics and computer vision technology. In addition to this, the increasing integration of mobile technologies with farming techniques, the growing usage of AI-based software to enhance farm efficiency, rising penetration of predictive analytics enabled software, and the increasing requirement for real-time management systems are bolstering the growth of the market.

Application- Segment Analysis

Based on the application, the precision farming segment is anticipated to lead the Global AI in Agriculture Market owing to the growing focus on increasing farm productivity driven by the rapid growth in the population rate and rising emphasis on upgrading food quality. Moreover, precision farming enables the farmer to make agriculture task more effective and predictable. Precision farming is one of the fastest-growing AI-enabled applications in agriculture. It helps farmers minimize costs and optimize resources effectively.   Agriculture robots operated by an AI system comprises field sensors and data analytics that can be effectively utilized for a range of applications.

In case, any of your paint points areas are not covered in the current scope of this report, Request for Customization here

Regional – Segment Analysis:

Based on the region, North America is expected to grow at a higher CAGR over the forecast period owing to the high penetration of industrial automation and artificial intelligence application in this region. The accelerated adoption of AI technology among large-scale agriculture players to enhance the speed and accuracy of crops in this region is further boosting the growth of the market in this region.

Asia Pacific is estimated to offer faster CAGR over the forecast period, because of the increasing adoption of artificial intelligence technologies in agriculture. Developing nations such as India and China have leveraged the adoption of artificial intelligence solutions like remote monitoring technology and predictive analysis in the food industry, bolstering the market growth. Furthermore, the growing demand to establish smart cities has encouraged agribusiness companies to deploy AI-leveraging solutions and services , bolstering the regional growth.

Top Market Players

Various notable players in the Artificial Intelligence in Agriculture Market include IBM Corporation, Deere & Company, Microsoft Corporation, The Climate Corporation (Subsidiary of Monsanto), Granular Inc., Descartes Labs, Inc., Prospera Technologies, AgEagle Aerial Systems Inc., Taranis, aWhere Inc., GAMAYA, among others.

Key Developments:

• • In Fen 2019, Prospera Technologies, an Israeli-based machine vision and artificial intelligence company, announced a partnership with Valmont Industries, Inc., a product and service provider for infrastructure and equipment for agriculture. The partnership aims to deliver farmers with autonomous crop management solutions, thereby generating higher revenues even from fewer production inputs and capitals. With this partnership, both the companies have combined artificial intelligence technologies with center pivot irrigation.
  • In Jul 2018, AgEagle signed an agreement to acquire Agribotix, an agriculture analytical company, to expand its imagery and data analytics offerings. With this acquisition, the company planned to integrate Agribotix’s FarmLens data analytics platform within AgEagle’s service offerings.

The Global Artificial Intelligence in Agriculture Market has been segmented based on the offering, technology, application, and region. Based on the offering, the market is categorized into hardware, software, ai-as-a-service, and service. Based on the hardware, the market is further segmented into a yield monitoring, field mapping, crop scouting, weather tracking and forecasting, and irrigation management. Based on software, the market is segmented into an AI platform and AI solution. Based on services, the market is segmented into deployment and integration, and support & maintenance. Based on technology, the market is segmented into machine learning, computer vision, and predictive analytics. Based on the application, the market is further segmented into precision farming, livestock monitoring, drone analytics, agriculture robots, and other application. Based on other applications, the market is segmented into smart greenhouse applications, soil management, and fish farming application.

For detailed scope of the “Artificial Intelligence in Agriculture Market” report request a Sample Copy of the report

Key questions answered in this research report:

• • At what pace is the Global Artificial Intelligence in Agriculture Market growing? What will be a growing trend in the future?
  • What are the key drivers and restraints in the Global Artificial Intelligence in Agriculture Market? What will be the impact of drivers and restraints in the future?
  • What are the regional revenue and forecast breakdowns? Which are the major regional revenue pockets for growth in the Global Artificial Intelligence in Agriculture Market?
  • What are the various application areas of the Global Artificial Intelligence in Agriculture Market, and how they are poised to grow?
  • Which Offering generated maximum revenues in 2019 and identify the most promising Offering during the forecast period?
  • What companies are the major participants in this market and their business strategies, how does the competitive landscape look like?

Market Segmentation

Global Artificial Intelligence in Agriculture Market by Offering            

• • Hardware
    • Processor
    • Storage Device
    • Network
  • Software
    • AI Platform
    • AI Solution
  • AI-as-a-Service
  • Service
    • Deployment and Integration
    • Support and Maintenance

Global Artificial Intelligence in Agriculture Market by Technology

• • Machine Learning
  • Computer Vision
  • Predictive Analytics

Global Artificial Intelligence in Agriculture Market by Application

• • Precision Farming
    • Yield Monitoring
    • Field Mapping
    • Crop Scouting
    • Weather Tracking and Forecasting
    • Irrigation Management
  • Livestock Monitoring
  • Drone Analytics
  • Agriculture Robots
  • Other Applications
    • Smart Greenhouse Applications
    • Soil Management
      • Moisture Monitoring
      • Nutrient Monitoring
    • Fish Farming Application

Global Artificial Intelligence in Agriculture Market by Region

• • North America Artificial Intelligence in Agriculture Market (Option 1: As a part of the free 25% customization)
    • By Offering
    • By Technology
    • By Application
    • US Market All-Up
    • Canada Market All-Up
  • Europe Artificial Intelligence in Agriculture Market (Option 2: As a part of the free 25% customization)
    • By Offering
    • By Technology
    • By Application
    • UK Market All-Up
    • Germany All-Up Market All-Up
    • France Market All-Up
    • Spain Market All-Up
    • Rest of Europe Market All-Up
  • Asia-Pacific Artificial Intelligence in Agriculture Market (Option 3: As a part of the free 25% customization)
    • By Offering
    • By Technology
    • By Application
    • China Market All-Up
    • India Market All-Up
    • Japan Market All-Up
    • Rest of APAC Market All-Up
  • RoW Artificial Intelligence in Agriculture Market (Option 4: As a part of the free 25% customization)
    • By Offering
    • By Technology
    • By Application
    • Brazil Market All-Up
    • South Africa Market All-Up
    • Saudi Arabia Market All-Up
    • UAE Market All-Up
    • Rest of world (remaining countries of the LAMEA region) Market All-Up

Major Players Operating the Artificial Intelligence in Agriculture (Option 5: As a part of the Free 25% Customization – Profiles of 5 Additional Companies of your Choice)

• • IBM Corporation
  • Deere & Company
  • Microsoft Corporation
  • The Climate Corporation (Subsidiary of Monsanto)
  • Granular Inc.
  • Descartes Labs, Inc.
  • Prospera Technologies
  • AgEagle Aerial Systems Inc.
  • Taranis
  • aWhere Inc.
  • GAMAYA