A comprehensive Artificial Intelligence in Agriculture Market research report delivers up-to-date data and insights, enabling businesses to strategize effectively in a rapidly evolving business landscape. Utilizing advanced analytical methods such as SWOT analysis and Porter's Five Forces, this report rigorously assesses both primary and secondary research findings. Additionally, the Artificial Intelligence in Agriculture market research report provides an in-depth analysis of the market’s current potential and future growth prospects, taking into account all pertinent industry factors.

Data Bridge Market Research analyses that the global artificial intelligence in agriculture market is expected to reach a value of USD 8.5 billion by 2031, at a CAGR of 22.4% during the forecast period. Global artificial intelligence in agriculture market report also comprehensively covers pricing analysis, patent analysis, and technological advancements.

Top Industry Players:

Deere & Company, IBM, Microsoft, Google, OpenAI, Open Text Corporation, ClimateAi,  AgEagle Aerial Systems Inc., CNH Industrial N.V., AGCO Corporation, KUBOTA Corporation, YANMAR HOLDINGS CO., LTD., DeLaval, Lely, Raven Industries, Inc., Gamaya, Bayer AG, VALMONT INDUSTRIES, INC., Cisco Systems, Inc., Oracle, Harvest CROO Robotics LLC, ADM, SYNGENTA GLOBAL, Corteva, and Bowery Farming Inc.

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Market Segmentation:

The artificial intelligence in agriculture market is segmented into five notable segments, which are based on the basis of offering, technology, application, deployment mode and end user. The growth amongst these segments will help you analyse meagre growth segments in the industries and provide the users with a valuable market overview and market insights to help them make strategic decisions for identifying core market applications.

This research report categorizes the global artificial intelligence in agriculture market into the following segments:

OFFERING

·HARDWARE

·SOFTWARE

·SERVICES

On the basis of offering, the market is segmented into hardware, software and services.

TECHNOLOGY

·MACHINE LEARNING (ML)

·COMPUTER VISION

·NATURAL LANGUAGE PROCESSING (NLP)

·ROBOTICS & AUTOMATION

·OTHERS

On the basis of technology, the market is segmented into machine learning (ML), computer vision, natural language processing (NLP), robotics & automation and others.

APPLICATION

·PRECISION FARMING

·LIVESTOCK MONITORING

·WEATHER FORECASTING

·SOIL MANAGEMENT

·CROP HEALTH MONITORING

·SUPPLY CHAIN OPTIMIZATION

·OTHERS

On the basis of application, the market is segmented into precision farming, livestock monitoring, weather forecasting, soil management, crop health monitoring, supply chain optimization and others.

DEPLOYMENT MODE

·CLOUD

·ON-PREMISE

On the basis of deployment mode, the market is segmented into cloud and on-premise.

END USER

·FARMS

·AGRO-TECH COMPANIES

·AGROCHEMICAL COMPANIES

·RESEARCH INSTITUTES

·OTHERS

On the basis of end user, the market is segmented into farms, agro-tech companies, agrochemical companies, research institutes and others.

The reputable Artificial Intelligence in Agriculture market report conducts a thorough competitive analysis, encompassing strategic profiling of key market players. It delves into their core competencies, strengths, weaknesses, and the overall competitive landscape. This in-depth examination supports businesses in illustrating their individual strategies effectively. The market research data provided in this report serves as a valuable resource for businesses in the planning of strategies related to investment, revenue generation, production, product launches, costing, inventory, purchasing, and marketing. With unwavering devotion and commitment, the Artificial Intelligence in Agriculture market survey report is presented with the utmost realism, offering trustworthy services and recommendations that businesses can confidently rely on.

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Strategic Points from Table of Content:

1.Introduction

-Objectives of the study
-Market definition
-Overview of global Artificial Intelligence in Agriculture market
-Currency and pricing
-Limitations
-Markets covered

2.Market segmentation

-Markets covered
-Geographical scope
-Years considered for the study
-DBMR tripod data validation model
-Primary interviews with key opinion leaders
-DBMR market position grid
-Vendor share analysis
-Multivariate modeling
-Offering timeline curve
-Market application coverage grid
-Secondary sources
-Assumptions

3.Executive summary

4.Premium insights

-Use case analysis
-Porters five forces analysis

5.Market overview

-Drivers
-Restraint
-Opportunities
-Challenges

6.Impact of covid-19 on the global Artificial Intelligence in Agriculture market

-Analysis on impact of covid-19 on the market
-Aftermath of covid-19
-Strategic decisions for manufacturers after covid-19 to gain competitive market share
-Impact on demand
-Conclusion

7.Global Artificial Intelligence in Agriculture market, by segment

-Overview

8.Global Artificial Intelligence in Agriculture market, company landscape

-Company share analysis: Global
-Company share analysis: North America
-Company share analysis: Europe
-Company share analysis: Asia pacific

9.Global Artificial Intelligence in Agriculture market, by region

10.Swot analysis

11.Company profile

-Company 1, 2, 3...

12.Questionnaire

13.Related reports

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