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The artificial intelligence (AI) market in agriculture market share is expected to increase by USD 458.68 million from 2020 to 2025, and the market's growth momentum will accelerate at a CAGR of 23.34%.
This artificial intelligence (AI) market in agriculture market research report provides valuable insights on the post COVID-19 impact on the market, which will help companies evaluate their business approaches. Furthermore, this report extensively covers artificial intelligence (AI) market in agriculture market segmentations by application (robotics, crop and soil management, and animal husbandry) and geography (North America, Europe, APAC, South America, and MEA). The artificial intelligence (AI) market in agriculture market report also offers information on several market vendors, including Ag Leader Technology, aWhere Inc., Corteva Inc., Deere & Co., DTN LLC, GAMAYA, International Business Machines Corp., Microsoft Corp., Raven Industries Inc., and Trimble Inc. among others.
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Maximizing profits in farm operations is notably driving the artificial intelligence (AI) market in agriculture market growth, although factors such as technical difficulties in developing AI technologies may impede the market growth. Our research analysts have studied the historical data and deduced the key market drivers and the COVID-19 pandemic impact on the artificial intelligence (AI) market in the agriculture market industry. The holistic analysis of the drivers will help in deducing end goals and refining marketing strategies to gain a competitive edge.
Key Artificial Intelligence (AI) Market In Agriculture Market Driver
Maximizing profits in farm operations is a major driver fueling the artificial intelligence market in agriculture market growth. To increase profits in farm operations, the yield and output of crops and animals must be maximized, respectively. AI technology incorporated in the form of robots, drones, crop management systems, and herd management tools enables farms to monitor and regulate remote operations and provide logical data to analyze several aspects of an agriculture farm. Smart or precision agriculture is rapidly emerging as a technology that will help farmers to enhance the deliverables in agriculture. With AI technologies on the rise, farmers can control and monitor the equipment, crop, and livestock through their smartphones and also receive statistical predictions for crops and livestock. Smart sensors, satellite imagery, and other cloud-based technologies are highly beneficial to observe and record data during crop planting and harvesting, thereby maximizing production output and minimizing the cost of resources wasted. In animal husbandry, advanced AI technologies, through sensors and visual imaging, can quickly analyze the health and physical well-being of a particular animal and flag deviations in case of any disease or ailment. In this way, the animal can be treated in due course of time without spreading the infection to other animals. Such timely monitoring also saves money, as the farmers need not wait for any symptom to arise in detecting abnormal animal health and take minor precautionary steps to induce recovery in the affected animal.
Key Artificial Intelligence (AI) Market In Agriculture Market Trend
Maximizing profits in farm operations is a major trend influencing the artificial intelligence market in agriculture market growth. To increase profits in farm operations, the yield and output of crops and animals must be maximized, respectively. AI technology incorporated in the form of robots, drones, crop management systems, and herd management tools enable farms to monitor and regulate remote operations and provide logical data to analyze several aspects of an agriculture farm. Smart or precision agriculture is rapidly emerging as a technology that will help farmers to enhance the deliverables in agriculture. With AI technologies on the rise, farmers can control and monitor the equipment, crop, and livestock through their smartphones and also receive statistical predictions for crops and livestock. Smart sensors, satellite imagery, and other cloud-based technologies are highly beneficial to observe and record data during crop planting and harvesting, thereby maximizing production output and minimizing the cost of resources wasted. In animal husbandry, advanced AI technologies, through sensors and visual imaging, can quickly analyze the health and physical well-being of a particular animal and flag deviations in case of any disease or ailment. In this way, the animal can be treated in due course of time without spreading the infection to other animals. Such timely monitoring also saves money, as the farmers need not wait for any symptom to arise in detecting abnormal animal health and take minor precautionary steps to induce recovery in the affected animal.
Key Artificial Intelligence (AI) Market In Agriculture Market Challenge
Technical difficulties in developing AI technologies are a major hindrance to the artificial intelligence market in agriculture market growth. AI-based technologies such as deep learning require voluminous data, as their knowledge base before these can be interpreted in real-time to make decisions. Acquisition of this data is an arduous process and may even be unethical. Also, smaller start-ups that specialize in AI may possess higher technical skills than large multinational companies such as Google or Microsoft but lack the funds to collect the necessary data. ?At present, AI is unable to multitask but can execute and adapt well to any situation that it may encounter while performing a single pre-programmed function rather than working for multiple functions with a re-programmable configuration. This is because the current neural network system cannot handle multiple functions simultaneously. Thus, more innovation is required to augment its functioning. Projects that are developing progressive neural networks are in the pipeline, which will allow the connection and communication of several deep learning systems for the transmission of new information and negate the need for re-programming.
This artificial intelligence (AI) market in agriculture market analysis report also provides detailed information on other upcoming trends and challenges that will have a far-reaching effect on the market growth. The actionable insights on the trends and challenges will help companies evaluate and develop growth strategies for 2021-2025.
Technavio categorizes the global artificial intelligence (AI) market in the agriculture industry as a part of the global industrial machinery market. Our research report has extensively covered external factors influencing the parent market growth potential in the coming years, which will determine the levels of growth of the artificial intelligence (AI) market in the agriculture market during the forecast period.
The report analyzes the market's competitive landscape and offers information on several market vendors, including:
This statistical study of the artificial intelligence (AI) market in agriculture market encompasses successful business strategies deployed by the key vendors. The artificial intelligence (AI) market in agriculture market is fragmented and the vendors are deploying growth strategies such as organic and inorganic strategies to compete in the market.
To make the most of the opportunities and recover from post COVID-19 impact, market vendors should focus more on the growth prospects in the fast-growing segments, while maintaining their positions in the slow-growing segments.
The artificial intelligence (AI) market in agriculture market forecast report offers in-depth insights into key vendor profiles. The profiles include information on the production, sustainability, and prospects of the leading companies.
Our report provides extensive information on the value chain analysis for the artificial intelligence (AI) market in agriculture market, which vendors can leverage to gain a competitive advantage during the forecast period. The end-to-end understanding of the value chain is essential in profit margin optimization and evaluation of business strategies. The data available in our value chain analysis segment can help vendors drive costs and enhance customer services during the forecast period.
The value chain of global industrial machinery includes the following core components:
The report has further elucidated on other innovative approaches being followed by service providers to ensure a sustainable market presence.
1 Executive Summary
2 Market Landscape
3 Market Sizing
4 Five Forces Analysis
5 Market Segmentation by Application
6 Customer landscape
7 Geographic Landscape
8 Drivers, Challenges, and Trends
9 Vendor Landscape
10 Vendor Analysis
11 Appendix
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