A New business Strategy report released by HTF MI with title Global Artificial Intelligence in Agriculture Market Study Forecast till 2030.

PUNE, MAHARASHTRA, INDIA, January 25, 2024 /EINPresswire.com/ -- The latest study released on the Global Artificial Intelligence in Agriculture Market by HTF MI evaluates market size, trend, and forecast to 2030.

The Artificial Intelligence in Agriculture market study covers significant research data and proofs to be a handy resource document for managers, analysts, industry experts and other key people to have ready-to-access and self-analyzed study to help understand market trends, growth drivers, opportunities and upcoming challenges and about the competitors.

Key Players in This Report Include :

IBM (United States), Deere & Company (United States), Intel (United States), Google (United States), Microsoft (United States), NVIDIA Corporation (United States), Sentient Technologies (United States), Numenta Inc. (United States), Agribotix (United States), The Climate Corporation (Subsidiary of Monsanto) (United States)

According to HTF Market Intelligence, the global Artificial Intelligence in Agriculture market is valued at USD 1.7 Billion in 2023 and estimated to reach a revenue of USD 5.9 Billion by 2030, with a CAGR of 23.05% from 2023 to 2030.

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Definition :

Artificial Intelligence (AI) in agriculture refers to the application of advanced computational techniques, machine learning algorithms, and data analytics to optimize various aspects of farming and agricultural practices. The goal is to enhance efficiency, productivity, and sustainability in crop cultivation, livestock management, and overall agricultural operations.

AI technologies in agriculture involve the use of computer systems that can analyze and interpret vast amounts of data, such as weather patterns, soil conditions, crop health, and historical yield data.

Market Trends :

Precision agriculture continued to be a prominent trend.
AI technologies were being used to enhance precision in resource management, including optimized use of water, fertilizers, and pesticides. This trend aimed at improving efficiency and sustainability in farming practices.

Market Drivers :

The need for precision in agriculture, aiming to optimize resource use and maximize yields, is a significant driver. AI enables farmers to analyze data with high granularity, allowing for precise decision-making in areas such as irrigation, fertilization, and pest control

Market Opportunities :

AI enables precision farming by analyzing vast amounts of data related to soil conditions, weather patterns, and crop health.

This allows farmers to optimize resource usage, leading to increased productivity and higher crop yields.

Target Audience :

New Entrants/Investors
Farmers
Automation and robotics
Logistics
Analysts and Strategic Business Planners
Venture and Capitalist
Government Research Organizations
Private Research Organization
End-Users
Others

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The Global Artificial Intelligence in Agriculture Market segments and Market Data Break Down are illuminated below :

Global Artificial Intelligence in Agriculture Market Breakdown
by Application (Weather Tracking, Precision Farming, Drone Analytics)
by Technology (Machine Learning, Computer Vision, Predictive Analytics) by Deployment Mode (Cloud, On-premises, Hybrid) and by Geography (North America, South America, Europe, Asia Pacific, MEA)

Global Artificial Intelligence in Agriculture market report highlights information regarding the current and future industry trends, growth patterns, as well as it offers business strategies to helps the stakeholders in making sound decisions that may help to ensure the profit trajectory over the forecast years.

Geographically, the detailed analysis of consumption, revenue, market share, and growth rate of the following regions :


• The Middle East and Africa (South Africa, Saudi Arabia, UAE, Israel, Egypt, etc.)
• North America (United States, Mexico & Canada)
• South America (Brazil, Venezuela, Argentina, Ecuador, Peru, Colombia, etc.)
• Europe (Turkey, Spain, Turkey, Netherlands Denmark, Belgium, Switzerland, Germany, Russia UK, Italy, France, etc.)
• Asia-Pacific (Taiwan, Hong Kong, Singapore, Vietnam, China, Malaysia, Japan, Philippines, Korea, Thailand, India, Indonesia, and Australia).


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Objectives of the Report :

• -To carefully analyze and forecast the size of the Artificial Intelligence in Agriculture market by value and volume.
• -To estimate the market shares of major segments of the Artificial Intelligence in Agriculture
• -To showcase the development of the Artificial Intelligence in Agriculture market in different parts of the world.
• -To analyze and study micro-markets in terms of their contributions to the Artificial Intelligence in Agriculture market, their prospects, and individual growth trends.
• -To offer precise and useful details about factors affecting the growth of the Artificial Intelligence in Agriculture
• -To provide a meticulous assessment of crucial business strategies used by leading companies operating in the Artificial Intelligence in Agriculture market, which include research and development, collaborations, agreements, partnerships, acquisitions, mergers, new developments, and product launches.


Major highlights from Table of Contents :

Artificial Intelligence in Agriculture Market Study Coverage :

• It includes major manufacturers, emerging player’s growth story, and major business segments of Artificial Intelligence in Agriculture market, years considered, and research objectives. Additionally, segmentation on the basis of the type of product, application, and technology.
• Artificial Intelligence in Agriculture Market Executive Summary: It gives a summary of overall studies, growth rate, available market, competitive landscape, market drivers, trends, and issues, and macroscopic indicators.
• Artificial Intelligence in Agriculture Market Production by Region Artificial Intelligence in Agriculture Market Profile of Manufacturers-players are studied on the basis of SWOT, their products, production, value, financials, and other vital factors.

• Key Points Covered in Artificial Intelligence in Agriculture Market Report :


• Artificial Intelligence in Agriculture Overview, Definition and Classification Market drivers and barriers
• Artificial Intelligence in Agriculture Market Competition by Manufacturers
• Impact Analysis of COVID-19 on Artificial Intelligence in Agriculture Market
• Artificial Intelligence in Agriculture Capacity, Production, Revenue (Value) by Region (2023-2030)
• Artificial Intelligence in Agriculture Supply (Production), Consumption, Export, Import by Region (2023-2030)
• Artificial Intelligence in Agriculture Production, Revenue (Value), Price Trend by Type {Machine Learning, Computer Vision, Predictive Analytic}
• Artificial Intelligence in Agriculture Manufacturers Profiles/Analysis Artificial Intelligence in Agriculture Manufacturing Cost Analysis, Industrial/Supply Chain Analysis, Sourcing Strategy and Downstream Buyers, Marketing

• Strategy by Key Manufacturers/Players, Connected Distributors/Traders Standardization, Regulatory and collaborative initiatives, Industry road map and value chain Market Effect Factors Analysis.

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Key questions answered :

How feasible is Artificial Intelligence in Agriculture market for long-term investment?
What are influencing factors driving the demand for Artificial Intelligence in Agriculture near future?
What is the impact analysis of various factors in the Global Artificial Intelligence in Agriculture market growth?
What are the recent trends in the regional market and how successful they are?

Thanks for reading this article; you can also get individual chapter wise section or region wise report version like North America, Middle East, Africa, Europe or LATAM, Southeast Asia.

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About Author :

HTF Market Intelligence Consulting is uniquely positioned to empower and inspire with research and consulting services to enable businesses with growth strategies, by offering services with extraordinary depth and breadth of thought leadership, research, tools, events, and experience that assist in decision-making.

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