Artificial Intelligence in Agriculture Market by Technology (Machine Learning, Computer Vision, and Predictive Analytics), Offering (Software, AI-as-a-Service), Application (Drone Analytics, Precision Farming) and Region - Global Forecast to 2028
The AI in agriculture market is projected to grow from USD 1.7 billion in 2023 to USD 4.7 billion in 2028; it is expected to grow at a CAGR of 23.1% during the forecasted period. AI in agriculture is mainly used in
precision farming, agriculture robots, livestock monitoring, drone analytics, labor management, and others. The market growth is mainly driven by government support to adopt modern agricultural techniques. Local governments in the Americas and Europe are encouraging farmers to adopt modern farming practices by providing improved budgets and guidance at different levels to increase food production. Governments worldwide are taking several initiatives to boost agriculture production, develop high-quality seeds, and increase storage capacities. These initiatives entail investing in AI-based farming technology.
“Market for AI-as-a-Service is to grow at highest CAGR during forecast period.”
The artificial intelligence (AI) in agriculture market has been segmented based on offering into hardware, software, AI-as-a-Service, and services. Market for AI-as-a-Service is expected to grow at highest CAGR during forecast period. Major companies, such as IBM, Microsoft, Granular, and Descartes Labs, are involved in providing AI-as-a-Service.
“Market for drone analytics application is expected to grow at highest CAGR during forecast period.”
The market for drone analytics application is expected to grow at highest CAGR during forecast period.
Drone support farmers by offering efficient plant protection, providing important data on soil types, and monitoring crop health. In agriculture, microdrones have a huge potential and a wide range of applications. Drone analytics software is used for measuring vegetation levels based on the normalized difference vegetation index (NDVI), a graphical indicator of this measurement.
“Market for Asia Pacific is to grow at highest CAGR during forecast period.”
The AI in agriculture market has been segmented into four geographic regions: the North America, Europe, Asia Pacific, and the Rest of the World (RoW). The market in Asia Pacific is expected to witness the highest growth rate during the forecast period. The wide-scale adoption of AI technologies in agricultural farming is a key factor supporting the growth of the market in this region. Further Asia Pacific is segmented into China, Japan, South Korea, India and Rest of Asia Pacific. There is an increasing application of AI in the agriculture sector in developing countries, such as India and China.
The report profiles key players in the AI in agriculture market with their respective market ranking analysis. Prominent players profiled in this report are Deere & Company (US), IBM (US), Microsoft (US), The Climate Corporation (US), Farmers Edge Inc. (Canada), Granular Inc. (Canada), AgEagle Aerial Syatems Inc. (US), Descartes Labs, Inc. (US).
Research Coverage:
This research report categorizes the AI in agriculture market on the basis Technology, Offering, Application, and Geography. The report describes the major drivers, restraints, challenges, and opportunities pertaining to the AI in agriculture market and forecasts the same till 2028. Apart from these, the report also consists of leadership mapping and analysis of all the companies included in the AI in agriculture ecosystem.
Key Benefits of Buying the Report
The report will help market leaders/new entrants in this market with information on the closest approximations of the revenue numbers for the overall AI in agriculture market and the subsegments. This report will help stakeholders understand the competitive landscape and gain more insights to better position their businesses and plan suitable go-to-market strategies. The report also helps stakeholders understand the pulse of the market and provides them with information on key market drivers, restraints, challenges, and opportunities.
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