Global Artificial Intelligence in Agriculture Markets Report 2023-2028 Featuring Key Players – Deere & Co, IBM, Microsoft, Climate Corp, Farmers Edge, Granular, AgEagle Aerial Syatems, Descartes Labs

DUBLIN, July 24, 2023 /PRNewswire/ — The “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” report has been added to’s offering.

The AI in the 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%

Artificial intelligence (AI) refers to the capability of a machine to perform tasks that usually require human intelligence. In the agriculture sector, it provides intelligent solutions that help farmers to grow crops more efficiently. The adoption of AI in agriculture adds significant value to the entire farm and the consumer supply chain.

The combination of the Internet of Things (IoT) and advanced analytics through AI allows farmers to analyze real-time data on weather conditions, temperatures, moisture levels, and crop prices in the market.

AI also involves the application of technologies and tools to enhance productivity and profitability in dairy farming. It is used in various agricultural applications, such as precision farming, livestock monitoring, agriculture robotics, and drone analytics.

Report Highlights:

AI-as-a-Service to Witness Highest CAGR Growth:

The market for AI-as-a-Service is expected to experience the highest compound annual growth rate (CAGR) during the forecast period. Leading companies like IBM, Microsoft, Granular, and Descartes Labs are actively involved in providing AI-as-a-Service solutions to cater to the evolving needs of the agriculture sector.

Drone Analytics Applications Set for Rapid Expansion:

The market for drone analytics applications is projected to witness the highest CAGR during the forecast period. Drones play a crucial role in supporting farmers by efficiently protecting crops, offering vital soil data, and monitoring overall crop health. The vast potential of microdrones in agriculture showcases a wide range of applications, with drone analytics software utilizing the normalized difference vegetation index (NDVI) for precise vegetation level measurements.

Robust Growth in the Asia Pacific Market:

The Asia Pacific region is poised for significant growth, with the highest anticipated CAGR during the forecast period. The widespread adoption of AI technologies in agricultural farming serves as a key driving force behind the market’s expansion in this region. Within Asia Pacific, countries like China, Japan, South Korea, India, and the Rest of Asia Pacific show increasing application of AI in the agriculture sector, especially in developing countries like India and China.

Competitive landscape

The report profiles key players in AI in the agriculture market with their respective market ranking analyses. 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).

Premium Insights

  • Rising Use of Drones to Increase Farm Productivity and Profitability to Provide Opportunities for Players Offering AI-Powered Solutions
  • Computer Vision Technology to Register Highest CAGR in AI in Agriculture Market Between 2023 and 2028
  • US and Drone Analytics to Account for Largest Share of AI in Agriculture Market in North America in 2028
  • Asia-Pacific to Record Highest CAGR in AI in Agriculture Market During Forecast Period

Market Dynamics


  • Adoption of Newer Technologies in Arable Land to Balance Food Supply and Population Increase
  • Rising Need for Real-Time Data by Growers and Farmers to Take Preventive Measures
  • Increasing Crop Productivity Through Deep Learning Technology
  • Government Support to Adopt Modern Agricultural Techniques
  • Increasing Use of AI-Enabled Robots and Automation in Agriculture due to Labor Shortage


  • High Cost of AI-Driven Precision Farming Equipment


  • Potential Growth Opportunities in Developing Countries
  • Government Schemes Encouraging Adoption of AI Solutions to Manage Small Farms
  • Rising Use of Drones to Increase Farm Productivity and Profitability


  • Interoperability Issues due to Lack of Standardization of Communication Protocols
  • Availability of Limited Workforce with Technological Expertise
  • Insufficient Historical Data to Build Predictive Models

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