Artificial Intelligence in Agriculture Market- by Solution Type (Machine Learning, Computer Vision, Predictive Analytics, Remote Sensing, Others), Offering (Software, Hardware, Services), Farming Type (Indoor Farming, Outdoor Farming), Deployment (Cloud-based, On-premises), Application (Precision Farming, Drone Analytics, Livestock Monitoring, Crop Monitoring, Agricultural Robots, Soil Management, Others), End-User and Region – Global Forecast to 2030

Industry : Electronics & Semiconductors | Pages : 180 Pages | Published On : Dec 2023

         
     

The Artificial Intelligence in Agriculture Market size is estimated to grow from USD 1.6 Billion in 2023 to reach USD 4.8 Billion by 2030, growing at a CAGR of 22.9% during the forecast period from 2023 to 2030.

Major players in Artificial Intelligence in Agriculture Market include: John Deere, IBM Corporation, Microsoft Corporation, Trimble Inc., Ag Leader Technology, Descartes Labs, Granular, Inc. (Corteva Agriscience), Prospera Technologies, The Climate Corporation (Bayer), Taranis, GAMAYA, PrecisionHawk

Increasing Need for Improved Agricultural Productivity and Efficiency

One of the significant drivers for the AI in Agriculture market is the increasing need for improved agricultural productivity and efficiency. With a growing global population and limited arable land, the agricultural sector faces the challenge of meeting the rising demand for food while optimizing resource utilization. Artificial Intelligence technologies offer innovative solutions to address these challenges and enhance agricultural productivity.

AI-powered solutions enable farmers to make data-driven crop management, irrigation, fertilization, and pest control decisions. By leveraging machine learning algorithms, farmers can analyze vast amounts of data collected from sensors, drones, satellites, and other sources to gain insights into crop health, soil conditions, and weather patterns. These insights allow them to optimize inputs, minimize waste, and improve overall productivity.

For instance, predictive analytics algorithms can forecast crop yields, enabling farmers to plan harvests and optimize storage and distribution. Computer vision technology combined with robotics can automate tasks such as weed detection and crop monitoring, reducing the reliance on manual labor and increasing operational efficiency. These AI-based advancements empower farmers to achieve higher yields, reduce costs, and enhance sustainability.

Technological Advancements in AI and Machine Learning

Another key driver for the AI in Agriculture market is the rapid technological advancements in AI and machine learning. Recent years have witnessed significant progress in AI technologies, including advancements in deep learning algorithms, computer vision, and natural language processing. These advancements have unlocked new possibilities for applying AI in the agricultural domain.

Machine learning algorithms excel at processing and analyzing large datasets, enabling the development of AI systems capable of detecting patterns, predicting outcomes, and making autonomous decisions. These capabilities are highly beneficial in agriculture, where complex data from various sources, such as sensors, satellites, and historical records, need to be analyzed to drive actionable insights.

Furthermore, advancements in computer vision technologies have facilitated the development of AI-powered imaging systems that can analyze images and videos to identify plant diseases, detect nutrient deficiencies, and monitor crop growth stages. This allows for timely interventions, reducing crop losses and optimizing yield.

The progress in AI and machine learning has also been fueled by advancements in hardware capabilities, such as powerful processors and cloud computing infrastructure. These technological advancements have made it feasible to process and analyze vast amounts of agricultural data in real time, enabling faster and more accurate decision-making.

In conclusion, the increasing need for improved agricultural productivity and the rapid technological advancements in AI and machine learning are two major drivers propelling the growth of AI in the Agriculture market. By harnessing the power of AI, farmers can optimize their operations, enhance crop yields, and contribute to sustainable agricultural practices.

Regional Insight

North America currently dominates the AI in Agriculture market. The region's dominance can be attributed to several factors, including the presence of key market players, advanced technological infrastructure, and a strong focus on precision farming and sustainable agriculture practices. Countries like the United States and Canada have witnessed significant adoption of AI technologies in agriculture due to their large-scale commercial farming operations and the need for optimizing resource utilization.

Asia-Pacific is expected to experience substantial growth in the AI in Agriculture market. The region has a large agricultural sector and is witnessing rapid advancements in AI technologies. Countries like China, India, and Japan are investing in AI-driven agriculture solutions to address the challenges of increasing food demand, decreasing arable land, and labor shortages. Moreover, government initiatives promoting the adoption of AI in agriculture are further propelling market growth in the region.

China, in particular, is emerging as a significant player in AI-driven agriculture. The country has a large population to feed and faces environmental challenges. As a result, there is a strong focus on leveraging AI technologies to enhance agricultural productivity and sustainability. With its vast market potential and supportive government policies, China is expected to drive significant growth in the AI in Agriculture market.

India is also a promising market for AI in Agriculture, given its vast agricultural sector and the government's emphasis on modernizing the agriculture industry. The country is witnessing the adoption of AI-driven solutions for precision farming, crop monitoring, and yield optimization.

Overall, while North America currently dominates the AI in the Agriculture market, Asia-Pacific, with countries like China and India, is expected to witness substantial growth and become a key player in the coming years due to its large agricultural sector and increasing adoption of AI technologies.

The Artificial Intelligence in Agriculture Market research report provides an in-depth overview of the industry including market segmentation by Solution, Offering, Farming Type, Deployment, Application, End-User, and Region. Analysis of the global market with a special focus on high-growth applications in each vertical and fast-growing market segment. It includes a detailed competitive landscape with identification of the key players concerning each type of market, in-depth market share analysis with individual revenue, market shares, and top players’ rankings. Impact analysis of the market dynamics with factors currently driving and restraining the growth of the market, along with their impact in the short, medium, and long-term landscapes. Competitive intelligence from the company profiles, key player strategies, and game-changing developments such as new product launches, collaborations, expansions, investment analysis, mergers, and acquisitions. The market analysis focuses on revenue and forecast by region/countries and by application in terms of revenue forecast for the period 2023-2030.

The report further studies the market strategies of key players, recent development status, plans, and Artificial Intelligence in Agriculture Market trends across the world. Also, it splits the market segmentation further to deep dive into research and reveals company profile and prospects.

Major Classifications are as follows:

  • Solution Type:
    • Machine Learning
    • Computer Vision
    • Predictive Analytics
    • Remote Sensing
    • Others
  • Offering:
    • Software
    • Hardware
    • Services
  • Farming Type:
    • Indoor Farming
    • Outdoor Farming
  • Deployment:
    • Cloud-based
    • On-premises
  • Application:
    • Precision Farming
    • Drone Analytics
    • Livestock Monitoring
    • Crop Monitoring
    • Agricultural Robots
    • Soil Management
    • Others
  • End User:
    • Farmers
    • Agricultural Cooperatives
    • Agriculture Equipment Manufacturers
    • Food Processing Companies
    • Research Organizations
    • Others
  • By Region
    • North America
      • US
      • Canada
    • Latin America
      • Brazil
      • Mexico
      • Argentina
      • Rest of Latin America
    • Europe
      • UK
      • Germany
      • France
      • Italy
      • Spain
      • Russia
      • Rest of Europe
    • Asia Pacific
      • China
      • Japan
      • India
      • South Korea
      • Rest of Asia Pacific
    • Rest of the World
      • Middle East
        • UAE
        • Saudi Arabia
        • Israel
        • Rest of the Middle East
      • Africa
        • South Africa
        • Rest of Middle East & Africa      

Reason to purchase this Artificial Intelligence in Agriculture Market Report:

  • Determine prospective investment areas based on a detailed trend analysis of the global Artificial Intelligence in the Agriculture Market over the next years.
  • Gain an in-depth understanding of the underlying factors driving demand for different Artificial Intelligence in Agriculture Market segments in the top spending countries across the world and identify the opportunities each offers.
  • Strengthen your understanding of the market in terms of demand drivers, industry trends, and the latest technological developments, among others.
  • Identify the major channels that are driving global Artificial Intelligence in the Agriculture Market, providing a clear picture of future opportunities that can be tapped, resulting in revenue expansion.
  • Channelize resources by focusing on the ongoing programs that are being undertaken by the different countries within the global Artificial Intelligence in Agriculture Market.
  • Make correct business decisions based on a thorough analysis of the total competitive landscape of the sector with detailed profiles of the top Artificial Intelligence in Agriculture Market providers worldwide, including information about their products, alliances, recent contract wins, and financial analysis wherever available.

TOC

  1. Executive Summary
  2. Introduction
    1. Key Takeaways
    2. Report Description
    3. Market Scope & Definition
    4. Stakeholders
    5. Research Methodology
      1. Market size
      2. Key data points from primary sources
      3. Key data points from secondary sources
      4. List of primary sources
      5. List of secondary sources
  3. Market Overview
    1. Introduction
    2. Industry Segmentation
    3. Market Trends Analysis
    4. Major Funding & Investments
    5. Market Dynamics
      1. Drivers
      2. Restraints
      3. Opportunities
    6. Value Chain Analysis
    7. Pricing Analysis
      1. Pricing Analysis, By Products
      2. Average Pricing Benchmark Analysis
  4. Artificial Intelligence in Agriculture Market, By Solution Type
    1. Machine Learning
    2. Computer Vision
    3. Predictive Analytics
    4. Remote Sensing
    5. Others
  5. Artificial Intelligence in Agriculture Market, By Offering
    1. Software
    2. Hardware
    3. Services
  6. Artificial Intelligence in Agriculture Market, By Farming Type
    1. Indoor Farming
    2. Outdoor Farming
  7. Artificial Intelligence in Agriculture Market, By Deployment
    1. Cloud-based
    2. On-premises
  8. Artificial Intelligence in Agriculture Market, By Application
    1. Precision Farming
    2. Drone Analytics
    3. Livestock Monitoring
    4. Crop Monitoring
    5. Agricultural Robots
    6. Soil Management
    7. Others
  9. Artificial Intelligence in Agriculture Market, By End-user
    1. Farmers
    2. Agricultural Cooperatives
    3. Agriculture Equipment Manufacturers
    4. Food Processing Companies
    5. Research Organizations
    6. Others
  10. Artificial Intelligence in Agriculture Market, By Geography
    1. Artificial Intelligence in Agriculture Market, North America
      1. U.S.
      2. Canada
    2. Artificial Intelligence in Agriculture Market, Latin America
      1. Brazil
      2. Mexico
      3. Argentina
      4. Rest of Latin America
    3. Artificial Intelligence in Agriculture Market, Europe
      1. UK
      2. Germany
      3. France
      4. Italy
      5. Spain
      6. Russia
      7. Rest of Europe
    4. Artificial Intelligence in Agriculture Market, Asia Pacific
      1. China
      2. Japan
      3. India
      4. South Korea
      5. Rest of Asia Pacific
    5. Artificial Intelligence in Agriculture Market, Rest of the world
      1. Middle East
        1. UAE
        2. Saudi Arabia
        3. Israel
      2. Africa
        1. South Africa
        2. Rest of Africa
  11. Competitive Analysis
    1. Introduction
    2. Top Companies Ranking
    3. Competitive Landscape
      1. Competition Dashboard
      2. Market Share Analysis (2022)
      3. Emerging company case studies
    4. Company Profiles
      1. John Deere
        1. Business Overview
        2. Product Portfolio
        3. Market Segments (Business Segment/Region)
        4. Sales Footprint
        5. Recent Developments
          1. New Product Launch
          2. Mergers & Acquisitions
          3. Collaborations, Partnerships & Agreements
          4. Rewards & Recognition
      2. IBM Corporation
        1. Business Overview
        2. Product Portfolio
        3. Market Segments (Business Segment/Region)
        4. Sales Footprint
        5. Recent Developments
          1. New Product Launch
          2. Mergers & Acquisitions
          3. Collaborations, Partnerships & Agreements
          4. Rewards & Recognition
      3. Microsoft Corporation
        1. Business Overview
        2. Product Portfolio
        3. Market Segments (Business Segment/Region)
        4. Sales Footprint
        5. Recent Developments
          1. New Product Launch
          2. Mergers & Acquisitions
          3. Collaborations, Partnerships & Agreements
          4. Rewards & Recognition
      4. Trimble Inc.
        1. Business Overview
        2. Product Portfolio
        3. Market Segments (Business Segment/Region)
        4. Sales Footprint
        5. Recent Developments
          1. New Product Launch
          2. Mergers & Acquisitions
          3. Collaborations, Partnerships & Agreements
          4. Rewards & Recognition
      5. Ag Leader Technology
        1. Business Overview
        2. Product Portfolio
        3. Market Segments (Business Segment/Region)
        4. Sales Footprint
        5. Recent Developments
          1. New Product Launch
          2. Mergers & Acquisitions
          3. Collaborations, Partnerships & Agreements
          4. Rewards & Recognition
      6. Descartes Labs
        1. Business Overview
        2. Product Portfolio
        3. Market Segments (Business Segment/Region)
        4. Sales Footprint
        5. Recent Developments
          1. New Product Launch
          2. Mergers & Acquisitions
          3. Collaborations, Partnerships & Agreements
          4. Rewards & Recognition
      7. Granular, Inc. (Corteva Agriscience)
        1. Business Overview
        2. Product Portfolio
        3. Market Segments (Business Segment/Region)
        4. Sales Footprint
        5. Recent Developments
          1. New Product Launch
          2. Mergers & Acquisitions
          3. Collaborations, Partnerships & Agreements
          4. Rewards & Recognition
      8. Prospera Technologies
        1. Business Overview
        2. Product Portfolio
        3. Market Segments (Business Segment/Region)
        4. Sales Footprint
        5. Recent Developments
          1. New Product Launch
          2. Mergers & Acquisitions
          3. Collaborations, Partnerships & Agreements
          4. Rewards & Recognition
      9. The Climate Corporation (Bayer)
        1. Business Overview
        2. Product Portfolio
        3. Market Segments (Business Segment/Region)
        4. Sales Footprint
        5. Recent Developments
          1. New Product Launch
          2. Mergers & Acquisitions
          3. Collaborations, Partnerships & Agreements
          4. Rewards & Recognition
      10. Taranis
        1. Business Overview
        2. Product Portfolio
        3. Market Segments (Business Segment/Region)
        4. Sales Footprint
        5. Recent Developments
          1. New Product Launch
          2. Mergers & Acquisitions
          3. Collaborations, Partnerships & Agreements
          4. Rewards & Recognition
      11. GAMAYA
        1. Business Overview
        2. Product Portfolio
        3. Market Segments (Business Segment/Region)
        4. Sales Footprint
        5. Recent Developments
          1. New Product Launch
          2. Mergers & Acquisitions
          3. Collaborations, Partnerships & Agreements
          4. Rewards & Recognition
      12. PrecisionHawk
        1. Business Overview
        2. Product Portfolio
        3. Market Segments (Business Segment/Region)
        4. Sales Footprint
        5. Recent Developments
          1. New Product Launch
          2. Mergers & Acquisitions
          3. Collaborations, Partnerships & Agreements
          4. Rewards & Recognition

Table and Figures

Methodology:

At MarketDigits, we take immense pride in our 360° Research Methodology, which serves as the cornerstone of our research process. It represents a rigorous and comprehensive approach that goes beyond traditional methods to provide a holistic understanding of industry dynamics.

This methodology is built upon the integration of all seven research methodologies developed by MarketDigits, a renowned global research and consulting firm. By leveraging the collective strength of these methodologies, we are able to deliver a 360° view of the challenges, trends, and issues impacting your industry.

The first step of our 360° Research Methodology™ involves conducting extensive primary research, which involves gathering first-hand information through interviews, surveys, and interactions with industry experts, key stakeholders, and market participants. This approach enables us to gather valuable insights and perspectives directly from the source.

Secondary research is another crucial component of our methodology. It involves a deep dive into various data sources, including industry reports, market databases, scholarly articles, and regulatory documents. This helps us gather a wide range of information, validate findings, and provide a comprehensive understanding of the industry landscape.

Furthermore, our methodology incorporates technology-based research techniques, such as data mining, text analytics, and predictive modelling, to uncover hidden patterns, correlations, and trends within the data. This data-driven approach enhances the accuracy and reliability of our analysis, enabling us to make informed and actionable recommendations.

In addition, our analysts bring their industry expertise and domain knowledge to bear on the research process. Their deep understanding of market dynamics, emerging trends, and future prospects allows for insightful interpretation of the data and identification of strategic opportunities.

To ensure the highest level of quality and reliability, our research process undergoes rigorous validation and verification. This includes cross-referencing and triangulation of data from multiple sources, as well as peer reviews and expert consultations.

The result of our 360° Research Methodology is a comprehensive and robust research report that empowers you to make well-informed business decisions. It provides a panoramic view of the industry landscape, helping you navigate challenges, seize opportunities, and stay ahead of the competition.

In summary, our 360° Research Methodology is designed to provide you with a deep understanding of your industry by integrating various research techniques, industry expertise, and data-driven analysis. It ensures that every business decision you make is based on a well-triangulated and comprehensive research experience.

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