North America Artificial Intelligence in Agriculture Market
North America Artificial Intelligence in Agriculture Market is growing at a CAGR of 21.8% to reach US$ 3,126.97 Million by 2030 from US$ 644.45 Million in 2022 by Component and Application.

Published On: Aug 2024

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North America Artificial Intelligence in Agriculture Market

At 21.8% CAGR, North America Artificial Intelligence in Agriculture Market is Projected to be Worth US$ 3,126.97 Million by 2030, says Business Market Insights

According to Business Market Insights' research, the North America artificial intelligence in agriculture market was valued at US$ 644.45 million in 2022 and is expected to reach US$ 3,126.97 million by 2030, registering a CAGR of 21.8% from 2022 to 2030. Robotics and automation in agriculture and growing use of unmanned ariel vehicles (UAVs) in farming are among the critical factors attributed to drive the North America artificial intelligence in agriculture market growth.

Robotics and automation have become essential components of farming and food production processes as the agricultural industry is constantly looking for ways to boost output, enhance efficiency, and decrease waste. Robots have a wide range of applications in agriculture, from complicated jobs such as crop monitoring and soil pH measurement to simpler chores such as harvesting and packing fruits and vegetables and planting seeds. Farmers have begun to experiment with self-contained systems that automate or supplement tasks such as pruning, harvesting, spraying, mowing, and weed eradication. Various committees are conducting research on robotics and automation in agriculture. For example, the Technical Committee for Agricultural Robotics and Automation (AgRA) promotes R&D, standardization, and innovation in robotics and automation to enable efficient, safe, and cost-effective agricultural production. The incorporation of AI technologies into robotic and automation systems improves their capabilities and empowers them to do more complicated jobs. AI gives robots a computer vision to sense, navigate, and calculate their reaction accordingly. Thus, the increasing deployment of AI in robotics and automation is anticipated to remain a trend in the AI in agriculture market.

On the flip side, shortage of technically skilled labor hampers the growth of North America artificial intelligence in agriculture market.

Based on component, the North America artificial intelligence in agriculture market is categorized into hardware, software, and services. The software segment held 65.9% market share in 2022, amassing US$ 424.50 million. It is projected to garner US$ 2,135.97 million by 2030 to register 22.4% CAGR during 2022-2030.

In terms of application, the North America artificial intelligence in agriculture market is segmented into precision farming, drone analytics, agriculture robots, livestock monitoring, and others. The precision farming segment held 39.2% share of North America artificial intelligence in agriculture market in 2022, amassing US$ 252.67 million. It is anticipated to garner US$ 1,195.38 million by 2030 to expand at 21.4% CAGR during 2022-2030.

Based on country, the North America artificial intelligence in agriculture market is categorized into the US, Canada, and Mexico. Our regional analysis states that the US captured 81.0% share of North America artificial intelligence in agriculture market in 2022. It was assessed at US$ 521.87 million in 2022 and is likely to hit US$ 2,567.24 million by 2030, registering a CAGR of 22.0% during 2022-2030.

Key players operating in the North America artificial intelligence in agriculture market are Deere & Co, Climate LLC, International Business Machines Corp, Microsoft Corp, and Taranis, among others.

  • In November 2022, Microsoft's research wing, in collaboration with Oxford University, Artificial Technology and Climate Change, Atal incubation center, and Agricultural Development Trust, has launched Microsoft Farmvibes.ai. It will focus on sustainable and cost-effective agricultural practices, utilizing precise scientific techniques and data-driven production.

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