AI in Agricultur Market Insights, Potential Business Strategies, Mergers and Acquisitions, Revenue Analysis

The artificial intelligence (AI) in agriculture market is advancing on account of the growing demand for crops, usage of internet of things (IoT), requirement for livestock monitoring, and adoption of drones in farms. In 2018, the market valued $584.0 million, from where it is predicted to progress to almost $4.0 billion by 2024 at a 38.3% CAGR during the forecast period (2019-2024). AI helps devices study the situations they are working in and learn from them and auto-correct their errors. In agriculture, AI helps better manage the planting, maintenance, and harvesting of crops.

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On segmenting by technology, the market is divided into predictive analysis, computer vision, and machine learning. Among these, the machine learning division led the AI in agriculture market during the historical period (2014-2018) and it set to continue on this path throughout the forecast period. Machine learning vastly helps the agrarian community by combining data technologies with agronomic sciences. Additionally, the rising adoption of IT for crop, field condition, and livestock management is spurring the growth of machine learning.

As with IoT, a large amount of unstructured and structured data can be handled, it is being increasingly used in agriculture. For instance, farmers get precise information regarding crop yield, rainfall, pest infestation, and soil nutrition from IoT-enabled sensors, which can help them in improving their farming techniques and the quality of the crops. Further, with the boom in population, the demand for crops is increasing, which is driving the adoption of AI.

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The United Nations has estimated that the worldwide population will reach 8.6 billion by 2030. With farmers facing intense pressure to maximize their yield, they are rapidly turning to IoT as well as AI. For instance, the ET Agricultural Brain, launched by Alibaba in 2018, is becoming popular as it lets farmers store the information about their crop yield digitally to make their production cycle more efficient. Similarly, that year, the NITI Aayog of the Indian government partnered with a leading AI in agriculture market player, IBM Corporation, to provide farmers with real-time advisory.

Based on application, the market is majorly categorized into agricultural robots, precision farming, drone analytics, and livestock monitoring. Among these, the precision farming category led the market during the historical period and will hold on to its dominance in the forecast period. During the forecast period, the drone analytics category is predicted to grow with the highest CAGR in the AI in agriculture market, as such tools are being rapidly deployed for monitoring the health of crops.

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This release was published on openPR.