Market Executive Summary

Artificial Intelligence has become one of the most important technologies in every sector, including education, banking, robotics, agriculture, etc. In the agriculture sector, it is playing a very crucial role, and it is transforming the agriculture industry. Artificial Intelligence has improved crop production and real-time monitoring, harvesting, processing, and marketing.

Due to the COVID-19 pandemic, the global AI in Agriculture market size was US$ 672 million in 2022 and is forecast to a readjusted size of US$ 1606 million by 2029 with a CAGR of 12.8% during the forecast period 2023-2029. Fully considering the economic change by this health crisis, Machine Learning accounting for % of the AI in Agriculture global market in 2022, is projected to value US$ million by 2029, growing at a revised ?GR from 2023 to 2029. While Precision Farming segment is altered to an ?GR throughout this forecast period.

AI is widely used in this sector. For agriculture, Artificial Intelligence has become a revolutionary technology. It helps the farmers by yielding healthier crops, controlling pests, soil monitoring, and many more ways. The industry is turning to Artificial Intelligence technologies to help yield healthier crops, control pests, monitor soil, and growing conditions, organize data for farmers, help with the workload, and improve a wide range of agriculture-related tasks in the entire food supply chain.

Different hi-tech computer-based systems are designed to determine various important parameters such as weed detection, yield detection, crop quality, and many more. AI has come up with a new application called Plantix. It was developed by PEAT to identify deficiencies in soil, including plant pests and diseases. With the help of this application, farmers can get an idea to use better fertilizer which can improve the harvest quality.

With AI sensors, weed can be detected easily, and it also detects weed-affected areas. On finding such areas, herbicides can be precisely sprayed to reduce the use of herbicides and also saves time and crop. Different AI companies are building robots with AI and computer vision, which can precisely spray on weeds. The use of AI sprayers can widely reduce the number of chemicals to be used on fields, hence improving the quality of crops and also saving money. With help of Artificial Intelligence farmers can analyze weather conditions by using weather forecasting.

Robotics is being widely used in different sectors, mainly in manufacturing, to perform complex tasks. Nowadays, different AI companies are developing robots to be employed in the Agriculture sector. These AI robots are developed in such a way that they can perform multiple tasks in farming.

Based on technology, the AI in agriculture market has been classified into machine learning, computer vision, and predictive analytics. Machine learning held the largest market size owing to the growing adoption of this technology for various applications of agriculture such as precision farming, drone analytics, agriculture robots, and livestock monitoring.

The market research report offered here is a very useful resource that can help manufacturers, stakeholders, decision-makers, and other market participants to become familiar with every factor impacting the growth of the global AI in Agriculture market. The analysts authoring the report have closely studied key strategies adopted by top players of the global AI in Agriculture market. The report includes SWOT, and other market analyses to provide a clear and deep understanding of important aspects of the global AI in Agriculture market. Readers of the report can become informed about current and future trends of the global AI in Agriculture market and how they will impact market growth during the forecast period.

By Company

    Ag Leader Technology

    Trimble

    John Deere

    Iteris

    AGCO

    aWhere

    Gamaya

    Granular

    Raven Industries

    Prospera

    Skysquirrel Technologies

Segment by Type

    Machine Learning

    Computer Vision

    Predictive Analytics

Segment by Application

    Precision Farming

    Livestock Monitoring

    Drone Analytics

    Agriculture Robots

    Others

By Region

    North America

        U.S.

        Canada

    Europe

        Germany

        France

        U.K.

        Italy

        Russia

    Asia-Pacific

        China

        Japan

        South Korea

        India

        Australia

        Taiwan

        Indonesia

    Latin America

        Mexico

        Brazil

        Argentina

    Middle East & Africa

        Turkey

        Saudi Arabia

        U.A.E

Chapter Outline

Chapter 1: Introduces the report scope of the report, executive summary of different market segments (product type, application, etc.), including the market size of each market segment, future development potential, and so on.

Chapter 2: Revenue of AI in Agriculture in global and regional level.

Chapter 3: Detailed analysis of AI in Agriculture companies' competitive landscape, revenue, market share and industry ranking, latest development plan, merger, and acquisition information, etc.

Chapter 4: Provides the analysis of various market segments by type, covering the revenue, and development potential of each market segment, to help readers find the blue ocean market in different market segments.

Chapter 5: Provides the analysis of various market segments by application, covering the revenue, and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.

Chapter 6: North America (US & Canada) by type, by application and by country, revenue for each segment.

Chapter 7: Europe by type, by application and by country, revenue for each segment.

Chapter 8: Asia Pacific by type, by application and by region, revenue for each segment.

Chapter 9: Latin America by type, by application and by country, revenue for each segment.

Chapter 10: Middle East and Africa, by type, by application and by country, revenue for each segment.

Chapter 11: Provides profiles of key companies, introducing the basic situation of the main companies in the market in detail, including product descriptions and specifications, AI in Agriculture revenue, gross margin, and recent development, etc.

Chapter 12: Introduces the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by manufacturers in the industry, and the analysis of relevant policies in the industry.

Chapter 13: Research Findings and Conclusion