According to BlueWeave Consulting, The Global AI in Agriculture market is projected to reach the valuation of US$ 3013 million by the year 2026 by growing at a CAGR of 21.6%. Using AI in agriculture provides various focal points, such as maximizing product yields using machine learning and Image recognition methods. For example, the International Crops Research Institute for Semi-Arid Tropics (ICRISAT) partnered with Microsoft to develop an AI-based sowing app that sends sowing alerts to ranchers indicating the following date. Earlier technological innovations and the modernization of GPS make ranchers and agricultural specialist cooperatives expect that further changes would increase profitability. For example, in addition to the present non-military benefits offered by GPS, nations are preparing to upgrade a second and a third signal on GPS satellites. This execution of new flags will improve the quality and, in addition, the ability of farming activities, and in the coming years will increase the overall productivity.
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Driverless tractor is a technological development as these tractors can automatically steer using GPS-based technology, raise tools from the ground, identify a farm’s boundaries and can be remotely operated using a smartphone. A smaller fleet of automated tractors could increase farmers ‘ incomes by more than 10 per cent and increased farm labor costs. The market is driven by a rise in the adoption of cattle face recognition technology. Through applying advanced metrics including facial recognition systems for cattle and image classification combined with body condition score and feeding habits, dairy farms are now able to monitor all behavioral factors in a cattle group individually.
Increasing use of Unmanned Aerial Vehicles (UAVs) across agricultural farms is driving the market as the use of drones in the agricultural industry can be used in crop field scanning with compact multi-spectral imaging sensors, GPS map production through on-board cameras, heavy payload transport and monitoring of livestock with thermal camera-equipped drones, which increases the demand for UAVs.
Drones fitted with hyperspectral, multispectral, or thermal sensors can locate areas that require irrigation changes. When crops have begun to develop, these sensors can measure their vegetation index and health indicator via AI by measuring the heat signature of the crop. As the global population is projected to exceed XX billion by 2050, it is expected that agricultural consumption will increase by a massive ratio, where drones have now been mainstreamed for smart farming to assist farmers in a range of tasks from analysis and planning to actual crop planting, and subsequent field monitoring to determine health and growth.
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Followed by North America, high growth rates in Asia Pacific are expected in the coming years due to growing demand from developing nations such as India and China. In addition, increasing adoption of mechanical technology and IoT gadgets in agriculture is also evaluated in order to drive the AI in the agricultural industry. In addition, Europe is leading in the agricultural sector with a lucrative pace in global AI. Farmers are managing nearly half of the European land area, making agriculture a dominant sector in Europe.
Artificial intelligence in Agriculture market is fragmented owing to the presence of number of large-sized companies, mid-sized & small-sized companies, and many start-ups that provide artificial intelligence in Agriculture industry. However, the companies that hold the majority share of artificial intelligence in Agriculture market are IBM Corporation, Microsoft Corporation, Bayer AG, Deere & Company, A.A.A. Taranis Visual Ltd, AgEagle Aerial Systems Inc., AGCO Corporation, Raven Industries, Ag Leader Technology, Trimble Inc., Google LLC, Gamaya SA, Granular Inc., PrecisionHawk, SAP and Other Prominent Players.
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