United States AI in Agriculture Market growth is driven by rising demand for precision farming, advancements in sensor technologies, and IoT integration from 2026 to 2030.
According to the TechSci Research report, “United States AI in Agriculture Market – By Region and Competition, Forecast & Opportunities, 2030F,” the United States AI in Agriculture Market stood at USD 351.09 Million in 2023. The market is expected to experience steady growth in the forecast period, with a CAGR of 12.30% through 2030. Several key factors are contributing to the growth of the AI in Agriculture market in the U.S. The increasing population is driving demand for agricultural products, and AI is playing a crucial role in improving production efficiency to meet this demand.
Additionally, there is a significant shift toward precision agriculture, where AI is used to optimize resource utilization and increase output. The availability of high-speed internet in rural areas further supports the adoption of AI technologies, and government initiatives are accelerating market expansion.
Research and development (R&D) activities are another key driver of the U.S. AI in Agriculture market’s growth. As the demand for efficient, sustainable farming practices rises, R&D efforts are focused on developing innovative AI solutions to optimize crop management, improve yield prediction, and enhance resource allocation. This has led to the creation of advanced AI algorithms and machine learning models that offer precision farming tools to monitor soil health, weather patterns, and pest control.
R&D is also accelerating the development of autonomous equipment, such as drones and robotic harvesters, that use AI to perform tasks more efficiently with less human intervention. Collaboration between academic institutions, private companies, and government agencies further fuels innovation, creating an environment conducive to breakthroughs in AI technologies for agriculture.
The United States AI in Agriculture Market is segmented into technology, offering, application, regional distribution, and companies. In terms of application, precision farming is currently dominating the market. This growth is largely due to its efficiency in resource utilization and its impact on improving crop yields. Precision farming uses AI technologies to monitor plant health, soil conditions, and weather patterns, enabling farmers to make informed decisions for optimizing productivity and sustainability. Machine learning algorithms analyze the collected data to deliver precise crop management recommendations.
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Additionally, remote sensing technologies, such as drones and satellite imagery, improve monitoring efforts. Real-time, detailed information helps farmers address issues like nutrient deficiencies or pest infestations, reducing crop losses and minimizing pesticide or fertilizer use. This practice also supports environmental sustainability by optimizing irrigation, conserving water, and preventing soil erosion.
Based on region, the West of the United States is emerging as the fastest-growing region in the AI in Agriculture market. The West is home to many technology hubs and agricultural research institutions, fostering innovation in AI-driven solutions tailored to farmers’ needs. The region’s diverse agricultural landscape, including crops like fruits, vegetables, and wine grapes, presents unique challenges that AI technologies can address, such as optimizing irrigation and improving pest management.
Major companies operating in the United States AI in Agriculture Market are:
- International Business Machines Corporation (IBM)
- Granular, Inc.
- Microsoft
- Deere & Company
- Awhere Inc.
- Climate LLC.
- Agribotix, LLC
- Descartes Labs Inc.
- Valmont Industries, Inc.
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“Nanomaterials, such as nanoparticles, are being used in sensors that can detect changes in soil composition, plant stress, and pest activity at a molecular level. These sensors, combined with AI analytics, provide real-time, actionable insights that allow farmers to make more informed decisions, reducing the need for excessive inputs like fertilizers and pesticides. This integration enhances the accuracy of AI algorithms, enabling more targeted interventions and ultimately increasing crop yields while minimizing environmental impact,” said Mr. Karan Chechi, Research Director of TechSci Research, a research-based management consulting firm.
“United States AI in Agriculture Market By Technology (Machine Learning, Predictive Analytics and Computer Vision), By Offering (Hardware, Software and AI-As-A-Service), By Application (Precision Farming, Livestock Monitoring, Agriculture Robots, Drone and Others), By Region, Competition, Forecast & Opportunities, 2019-2029F”, has evaluated the future growth potential of United States AI in Agriculture Market and provides statistics & information on market size, structure and future market growth. The report intends to provide cutting-edge market intelligence and help decision-makers take sound investment decisions. Besides, the report also identifies and analyzes the emerging trends along with essential drivers, challenges, and opportunities in United States AI in Agriculture Market.
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