Global AI in Agriculture Market Size study, by Application (Weather Tracking, Precision Farming, Drone Analytics) By Deployment (Cloud, On-premise, Hybrid) and Regional Forecasts 2022-2032

Global AI in Agriculture Market Size study, by Application (Weather Tracking, Precision Farming, Drone Analytics) By Deployment (Cloud, On-premise, Hybrid) and Regional Forecasts 2022-2032

Global AI in Agriculture Market is valued approximately at USD 1753.2 million in 2023 and is anticipated to grow with a healthy growth rate of more than 26.21% over the forecast period 2024-2032. AI in agriculture encompasses the adoption of machine learning algorithms, computer vision, robotics, and other AI techniques to improve agricultural production, resource management, crop health monitoring, task automation, and data-driven decision-making. AI in agriculture seeks to improve efficiency, production, and sustainability in farming while lowering costs and adverse environmental effects. Furthermore, rising integration of drone analytics are gaining attention towards Global AI in Agriculture Market. Drones equipped with cameras and sensors can collect high-resolution imagery and data over large agricultural areas. AI algorithms can then analyze this data to provide farmers with valuable insights about crop health, nutrient levels, water stress, pest infestations, and other factors.

The Global AI in Agriculture Market is driven by rising demand for precision farming techniques and increase use of unmanned aerial vehicles (UAVs) within agricultural farms across the world. Precision farming techniques streamline farm operations and improve overall efficiency. By automating repetitive tasks such as field monitoring, irrigation scheduling, and pest detection, AI technologies reduce the need for manual labor and enable farmers to focus their efforts on more strategic activities. In addition, UAVs enable precision agriculture by providing farmers with detailed, real-time information about their fields. AI algorithms can analyze the data collected by drones to create detailed maps and models of the farm, identifying areas of variability, and optimizing input application. However, high deployment cost of AI in Agriculture and lack of standardization in data collection is going to impede the overall demand for the market during the forecast period 2022-2032.

The key regions considered for the Global AI in Agriculture market study includes Asia Pacific, North America, Europe, Latin America, and Rest of the World. In 2023, North America was the largest regional market in terms of revenue owing to factors such as increasing adoption of AI technologies to enhance agricultural productivity across the region. AI-powered systems help farmers optimize the use of inputs such as water, fertilizers, and pesticides by providing real-time monitoring and analysis of crop conditions. Furthermore, the market in Asia Pacific, on the other hand, is expected to grow at the fastest rate over the forecast period.

Major market player included in this report are:
Microsoft Corporation
International Business Machines Corporation
Granular Inc
aWhere Inc
Prospera Technologies Ltd
Gamaya SA
Easytosee Agtech, SL
PrecisionHawk Inc
Cainthus Corp
Tule Technologies Inc

The detailed segments and sub-segment of the market are explained below:

By Application
Weather Tracking
Precision Farming
Drone Analytics

By Deployment
Cloud
On-premise
Hybrid

By Region:
North America
U.S.
Canada
Europe
UK
Germany
France
Spain
Italy
ROE
Asia Pacific
China
India
Japan
Australia
South Korea
RoAPAC
Latin America
Brazil
Mexico
Middle East & Africa
Saudi Arabia
South Africa
RoMEA

Years considered for the study are as follows:
Historical year – 2022
Base year – 2023
Forecast period – 2024 to 2032

Key Takeaways:
Market Estimates & Forecast for 10 years from 2022 to 2032.
Annualized revenues and regional level analysis for each market segment.
Detailed analysis of geographical landscape with Country level analysis of major regions.
Competitive landscape with information on major players in the market.
Analysis of key business strategies and recommendations on future market approach.
Analysis of competitive structure of the market.
Demand side and supply side analysis of the market

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