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The AI in agriculture market is projected to grow at a CAGR of 25.5% from 2020 to 2026.
The overall AI in agriculture market is estimated to be USD 1.0 billion in 2020 and is projected to reach USD 4.0 billion by 2026, at a CAGR of 25.5% between 2020 and 2026. The market growth is propelled by the increasing implementation of data generation through sensors and aerial images for crops, increasing crop productivity through deep-learning technology, and government support for the adoption of modern agricultural techniques. However, the high cost of gathering precise field data restrains the market growth. Developing countries, such as China, Brazil, and India, are likely to provide an opportunity for the players in the AI in agriculture market due to the increasing use of unmanned aerial vehicles/drones by these countries in their agricultural farms.
By technology, the machine learning segment is estimated to account for the largest share of the AI in agriculture market during the forecast period.
Machine learning-enabled solutions are being significantly adopted by agricultural organizations and farmers worldwide to enhance farm productivity and to gain a competitive edge in business operations. In the coming years, the application of machine learning in various agricultural practices is expected to rise exponentially.
By offering, the AI-as-a-Service segment is projected to register the highest CAGR from 2020 to 2026.
Increasing demand for machine learning tool kits and applications that are available in AI-based services, along with benefits, such as advanced infrastructure at minimal cost, transparency in business operations, and better scalability, is leading to the growth of the AI-as-a-Service segment.
By application, the precision farming segment held the largest market size in 2019.
Precision farming involves the usage of innovative artificial intelligence (AI) technologies, such as machine learning, computer vision, and predictive analytics tools, for increasing agriculture productivity. It comprises a technology-driven analysis of data acquired from the fields for increasing crop productivity. Precision farming helps in managing variations in the field accurately, thus enabling the growth of more crops using fewer resources and at reduced production costs. Precision devices integrated with AI technologies help in collecting farm-related data, thereby helping the farmers make better decisions and increase the productivity of their lands
Breakdown of profiles of primary participants:
- By Company Type: Tier 1 – 35%, Tier 2 – 40%, and Tier 3 – 25%
- By Designation: C-level Executives – 57%, Directors – 29%, and Others – 14%
- By Region: Americas – 40%, Europe – 30%, Asia Pacific (APAC)– 20%, and Rest of the World (RoW) – 10%
International Business Machines Corp. (IBM) (US), Deere & Company (John Deere) (US), Microsoft Corporation (Microsoft) (US), Farmers Edge Inc. (Farmers Edge) (Canada), The Climate Corporation (Climate Corp.) (US), ec2ce (ec2ce) (Spain), Descartes Labs, Inc. (Descartes Labs) (US), AgEagle Aerial Systems (AgEagle) (US), and aWhere Inc. (aWhere) (US) are the prominent players in the AI in agriculture market
The AI in agriculture market has been segmented based on technology, offering, application, and geography.
Reasons To Buy the Report:
- This report includes statistics pertaining to the AI in agriculture market based on technology, offering, application, and geography.
- The report includes detailed information on major drivers, restraints, opportunities, and challenges pertaining to the market.
- The report also includes illustrative segmentation, analysis, and forecast for the AI in agriculture market based on its segments and subsegments.