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With the rapidly growing population worldwide, estimated to reach around a mammoth 10 Billion mark by 2050, the demand for food for sustenance has been and will continue to be on the rise. The increasing application of Artificial Intelligence in all sectors is expected to boost for the catering of the growing needs. In the Agricultural Sector, AI has been developing and already has a wide range of applications including precision farming, crop monitoring, crop analytics, and others done by robots, drones, and ground-based wireless sensors and other technological equipments. These help the stakeholders in optimum supply and fulfillment of the increasing demand. The AI in Agriculture market is expected to reach around $4 Billion by 2026 from $1 Billion in 2020 at a comprehensive CAGR of 25.5% during the period.
The growth of this market is attributed by major factors including rising demand for high crop yield, growing focus on enhanced crop management, increasing crop productivity by implementing deep learning techniques, increasing population, rising adoption of information management systems , increasing penetration of internet of things (IoT) in the agriculture industry , surging utilization of drones for pesticide spraying, etc.
Moreover, development of new products including agricultural drones with new technologies, such as weather data, advanced image recognition, and precise analysis, which have now been mainstreamed for smart farming, supporting farmers in a range of tasks from analysis and planning to the real planting of crops, and ensuing observing of fields to determine health and growth. For instance, Agrobotix LLC (now acquired by AgEagle Aerial Systems) is a drone enabled software company that provides quality imaging and data analysis for sustainable and precision agriculture, and is supporting over more than 53 crops, including corn, grape, apple, sugarcane, and so on for sustainable and precision farming across 50 countries.
Furthermore, 70-80% of the new equipment purchases have been deemed to contain some form of precision farming tools along with the demand of smart green applications. This, along with, increasing use of Unmanned Aerial Vehicles (UAVs) across agricultural farms is anticipated to boost the growth of artificial intelligence in the agriculture market.
However, high cost of systems and services, requirement of a lot of data to train machines to make accurate predictions, lack of standards and lack of awareness about use of artificial intelligence in agriculture sector in some underdeveloped and developing countries are some factors that restrain the growth of artificial intelligence in the agriculture market.
AI AGRICULTURE MARKET SEGMENTATION:
Based on Technology:
Based on Offering:
Based on Deployment:
Based on Application:
Based on region:
North America dominated the AI in agriculture industry and also generated the highest revenue in the AI agriculture market during the period (2014–2019).This is majorly attributed to the early adoption of technologies such as machine learning (ML) and computer vision for agricultural applications, including precision farming, livestock management, greenhouse management, and soil management. Moreover, certain players in the region are offering services to regional consumers by engaging in partnerships with other leading players. Companies such as IBM Corporation and Raven Industries Inc. are increasingly collaborating with other players, to enhance their offerings for the agriculture industry. Hence, with the increasing use of AI in agriculture, to deliver advanced analytical insights to farmers, the market is growing in this region and is expected to lead the global market, in terms of revenue, over the forecast period too.
The APAC region is expected to be the fastest growing region in terms of AI-enabled agricultural solutions. The growth can majorly be attributed to the high adoption rate of AI in the agriculture sector in major countries, such as China, India, Japan, and Australia. With India and China witnessing huge growth in the adoption of AI solutions in agriculture, owing to the increasing efforts made by the governments, as well as various multinational companies (MNCs), for spreading awareness about farm analytics and data sciences among Indian farmers and the entry of Alibaba Group in the agricultural solution business with its AI technology, to assist small farmers in the country, this region is expected to continue to grow at a more rapid rate.
European region is estimated to account for the largest market growth. Software and hardware solutions like 'Internet of the Soil' exist in this region, which is used for observing soil conditions like humidity, temperature, electrical conductivity. Few firms have urbanized vertical indoor farming systems using IoT, Big Data, and cloud analytics, which can be employed in supermarkets, restaurants, local distribution warehouses, permitting businesses to grow their own fresh crop on site to deliver to customers.
FEW KEY PLAYERS IN AI AGRICULTURE MARKET:
Timeline Considered for Analysis:
- 2019: Base Year
- 2019 to 2025: Forecast Period
Research Scope and Deliverables
Overview & Executive Summary
Market Drivers, Trends, Challenges and Opportunities
Market Size and Forecast Projections
Macroeconomic Indicators of Various Countries Impacting the Growth of the Market
Extensive Coverage of Industry Players including Recent Product Launches and Market Activities
Porter’s Five Force Analysis
Market Segmentation Analysis:
Industry report analyzes the global AI agriculture market by the following segments:
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Key Questions Answered in the Global AI agriculture Industry Report
The report offers a comprehensive insight on the AI agriculture Market share, competitor landscape, market trends, growth, revenue, and key driver’s analysis with coverage of key players, top geographies, product types and end user.
Exhaustive secondary research and in-depth primary interviews with industry experts has been conducted to present qualitative and quantitative insights in the report.
We offer customizations as per client’s specific needs.