Latest Study on Industrial Growth of AI in Agriculture Market 2024-2030. The report contains different market predictions related to revenue size, production, CAGR, Consumption, gross margin, price, and other substantial factors. While emphasizing the key driving and restraining forces for this market, the report also offers a complete study of the future trends and developments of the market. It also examines the role of the leading market players involved in the industry including their corporate overview, financial summary, and SWOT analysis.
The AI in Agriculture market size is estimated to reach by USD 5.17 Billion at a CAGR of 22.34% by 2030. The report includes historic market data from 2019 to 2023. The Current market value is pegged at USD 1.93 Billion.
The Major Players Covered in this Report: IBM (United States), John 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)
AI in Agriculture Market Study guarantees you to remain/stay advised higher than your competition. With Structured tables and figures examining the AI in Agriculture, the research document provides you with a leading product, submarkets, revenue size, and forecast for 2030. Comparatively, it also classifies emerging as well as leaders in the industry. Click To get SAMPLE PDF of AI in Agriculture Market (Including Full TOC, Table & Figures) @ https://www.htfmarketintelligence.com/sample-report/global-ai-in-agriculture-market
This study also covers company profiling, specifications and product picture, sales, market share, and contact information of various regional, international, and local vendors of AI in Agriculture Market. The market proposition is frequently developing ahead with the rise in scientific innovation and M&A activities in the industry. Additionally, many local and regional vendors are offering specific application products for varied end-users. The new merchant applicants in the market are finding it hard to compete with international vendors based on reliability, quality, and modernism in technology.
Definition:
The AI in Agriculture market refers to the use and application of Artificial Intelligence (AI) technologies and solutions in the agriculture sector. AI technologies are deployed to enhance various aspects of agricultural practices, including crop management, livestock monitoring, precision farming, and supply chain optimization. AI in Agriculture aims to improve efficiency, sustainability, and productivity in farming operations. AI is used for monitoring and managing crops by analyzing data from various sources such as drones, satellites, and sensors. It helps in detecting diseases, pests, and nutrient deficiencies, optimizing irrigation, and predicting crop yields. AI is applied to monitor the health and behavior of livestock. It involves using sensors, wearable devices, and computer vision to track animal movements, health indicators, and breeding patterns. AI enables precision farming techniques by providing real-time data on soil conditions, weather, and crop health. Farmers can make data-driven decisions to optimize planting, fertilization, and harvesting.
Market Trends:
- The adoption of precision agriculture techniques continued to grow, with AI enabling farmers to make data-driven decisions for precise planting, irrigation, and fertilization.
- The use of AI-powered remote sensing technologies, including drones and satellites, was increasing for crop monitoring, disease detection, and yield prediction.
- Robotics and AI-driven automation were gaining traction for tasks such as planting, weeding, and harvesting, reducing labor costs and improving efficiency.
Market Drivers:
- The need to feed a growing global population was a significant driver, prompting the adoption of AI to enhance crop yields and agricultural efficiency.
- Increasing emphasis on sustainable farming practices and environmental conservation drove the adoption of AI to reduce resource wastage and environmental impact.
- Advances in AI, machine learning, and IoT technologies provided new tools and solutions for agriculture.
Market Opportunities:
- Agricultural organizations and tech companies saw opportunities in monetizing data collected from farms, offering valuable insights to farmers and stakeholders.
- The global adoption of AI in Agriculture presented opportunities for technology providers to expand their offerings to different regions and emerging markets.
- There were opportunities for AI applications in livestock management, including health monitoring, breeding optimization, and feed management.
Market Challenges:
- Access to high-quality, reliable data and connectivity in rural areas remained a challenge, limiting the effectiveness of AI solutions.
- Some farmers faced challenges in terms of the initial cost of implementing AI technologies and the need for training.
- Concerns related to data privacy, ownership, and regulatory compliance added complexity to AI adoption in agriculture.
The titled segments and sub-section of the market are illuminated below:
In-depth analysis of AI in Agriculture market segments by Types: Product, Hardware, Software, Service, Professional, Managed
Detailed analysis of AI in Agriculture market segments by Applications: Precision Farming, Livestock Monitoring, Drone Analytics, Agriculture Robots, Other
For More Information Read Table of Content @ https://www.htfmarketintelligence.com/report/global-ai-in-agriculture-market
Major Key Players of the Market: IBM (United States), John 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)
Regional Analysis for AI in Agriculture Market:
• APAC (Japan, China, South Korea, Australia, India, and the Rest of APAC; the Rest of APAC is further segmented into Malaysia, Singapore, Indonesia, Thailand, New Zealand, Vietnam, and Sri Lanka)
• Europe (Germany, UK, France, Spain, Italy, Russia, Rest of Europe; Rest of Europe is further segmented into Belgium, Denmark, Austria, Norway, Sweden, The Netherlands, Poland, Czech Republic, Slovakia, Hungary, and Romania)
• North America (U.S., Canada, and Mexico)
• South America (Brazil, Chile, Argentina, Rest of South America)
• MEA (Saudi Arabia, UAE, South Africa)
Furthermore, the years considered for the study are as follows:
Historical year – 2019-2023
Base year – 2023
Forecast period** – 2024 to 2030 [** unless otherwise stated]
**Moreover, it will also include the opportunities available in micro markets for stakeholders to invest, a detailed analysis of the competitive landscape, and product services of key players.
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Key takeaways from the AI in Agriculture market report:
– Detailed consideration of AI in Agriculture market-particular drivers, Trends, constraints, Restraints, Opportunities, and major micro markets.
– Comprehensive valuation of all prospects and threats in the
– In-depth study of industry strategies for growth of the AI in Agriculture market-leading players.
– AI in Agriculture market latest innovations and major procedures.
– Favourable dip inside Vigorous high-tech and market latest trends remarkable the Market.
– Conclusive study about the growth conspiracy of AI in Agriculture market for forthcoming years.
What to Expect from this Report On AI in Agriculture Market:
1. A comprehensive summary of several area distributions and the summary types of popular products in the AI in Agriculture Market.
2. You can fix up the growing databases for your industry when you have info on the cost of the production, cost of the products, and cost of the production for the next years.
3. Thorough Evaluation of the break-in for new companies who want to enter the AI in Agriculture Market.
4. Exactly how do the most important companies and mid-level companies make income within the Market?
5. Complete research on the overall development within the AI in Agriculture Market that helps you select the product launch and overhaul growths.
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Detailed TOC of AI in Agriculture Market Research Report-
– AI in Agriculture Introduction and Market Overview
– AI in Agriculture Market, by Application [Precision Farming, Livestock Monitoring, Drone Analytics, Agriculture Robots, Other]
– AI in Agriculture Industry Chain Analysis
– AI in Agriculture Market, by Type [Product, Hardware, Software, Service, Professional, Managed]
– Industry Manufacture, Consumption, Export, Import by Regions (2019-2032E)
– Industry Value ($) by Region (2019-2032E)
– AI in Agriculture Market Status and SWOT Analysis by Regions
– Major Region of AI in Agriculture Market
i) AI in Agriculture Sales
ii) AI in Agriculture Revenue & market share
– Major Companies List
– Conclusion
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