HTF MI published a new business research study with the title Artificial Intelligence in Agriculture Market Study Forecast till 2030. This Artificial Intelligence in Agriculture market report brings data for the estimated year 2024 and forecasted till 2030 in terms of both, value (USD MN) and volume (MT). The report also consists of a detailed assessment of macroeconomic factors and a market outlook of the Artificial Intelligence in Agriculture market. The study is conducted by applying both top-down and bottom-up approaches and further iterative methods used to validate and size market estimation and trends of the Artificial Intelligence in Agriculture market. Additionally, to complement insights EXIM data, consumption, supply and demand Figures, raw price analysis, market revenue, and gross margins.
Some of the companies listed in the research study are 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)
The Artificial Intelligence in Agriculture Market have seen a market size of USD 3.5BILLION in 2023 and estimated to reach USD 12BILLION by 2030, growth at a CAGR of 18 %. Pre Covid, back in 2019 it was ranging ~ USD 1BILLION and since then market have recovered completely and showing robust growth.
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Definition:
AI technologies like predictive analytics, IoT, and drones applied to optimize agricultural productivity and resource efficiency.
Market Trends:
AI-powered robotics for harvesting, satellite-based crop health monitoring.
Market Drivers:
Rising food demand, need for precision farming, labor shortages.
Market Challenges:
High cost of implementation for small-scale farmers.
Fastest-Growing Region:
Asia-Pacific
Dominating Region:
North America
What to Expect from this Report On Artificial Intelligence in Agriculture Market:
1. A comprehensive summary of several area distributions and the summary types of popular products in the Artificial Intelligence 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 Artificial Intelligence 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 Artificial Intelligence in Agriculture Market that helps you select the product launch and overhaul growths.
Focus on segments and sub-sections of the Market are illuminated below:
Based on Product Types of Artificial Intelligence in Agriculture Market: Computer Vision, Machine Learning, IoT
The Study Explores the Key Applications/End-Users of Artificial Intelligence in Agriculture Market: Precision Farming, Crop Monitoring, Livestock Management
Regional Analysis for Artificial Intelligence 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)
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Resource and Consumption – In extension with sales, this segment studies Resources and consumption for the Artificial Intelligence in Agriculture Market. Import-export data is also provided by region if applicable.
Free Customization based on client requirements on Immediate purchase:
1- Free country-level breakdown of any 5 countries of your interest.
2- Competitive breakdown of segment revenue by market players.
3 – Additional company profiles and Qualitative analysis subject to feasibility check.
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