Artificial Intelligence in Agriculture Market Disclosing Technology Advancements, Growth and Future Scope 2021 to 2025

The report presents an in-depth assessment of the Artificial Intelligence in Agriculture Market including enabling technologies, key trends, market drivers, challenges, standardization, regulatory landscape, deployment models, operator case studies, opportunities, future roadmap, value chain, ecosystem player profiles and strategies. The report also presents forecasts for Artificial Intelligence in Agriculture from 2021 till 2025. The report covers the pre COVID-19 historic data, impact of COVID-19 and post-COVID-19 (Corona Virus) impact on various regions and major countries and on the future development of the industry is pointed out.

The global Artificial Intelligence in agriculture market is witnessing a CAGR of 26.2% during the forecast period (2021-2025).

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The report presents the market competitive landscape and a corresponding detailed analysis of the major vendor/key players in the market. Top Companies in the Global Artificial Intelligence in Agriculture Market: Microsoft Corporation, IBM Corporation, Granular, Inc., aWhere, Inc., Prospera Technologies Ltd., Gamaya SA, ec2ce, PrecisionHawk Inc., Cainthus Corp., Tule Technologies Inc. and others.

Key Developments:

May 2019 - XAG, a Chinese firm, presented its innovative solutions of combining drones with AI and IoT technology to achieve precision agriculture and induce transformational changes to the food system in 3rd AI for Good Global Summit, in Geneva. XAG is driving AI-powered intelligent devices such as drones and sensors to establish digital farming infrastructure in rural areas and enable precision agriculture which, for example, accurately targets pesticides, seeds, fertilizers, and water to wherever it is needed.

Market Overview:

- Maximize crop yield using machine learning technique is driving the market. Species selection is a tedious process of searching for specific genes that determine the effectiveness of water and nutrients use, adaptation to climate change, disease resistance, as well as nutrients content or a better taste. Machine learning, in particular, deep learning algorithms, take decades of field data to analyze crops performance in various climates and based on this data one can build a probability model that would predict which genes will most likely contribute a beneficial trait to a plant.
- Increase in the adoption of cattle face recognition technology is driving the market. Through the application of advanced metrics, including cattle facial recognition programs and image classification incorporated with body condition score and feeding patterns, dairy farms are now being able to individually monitor all behavioral aspects in a group of cattle.
- However, lack of standardization is restraining the market growth as lack of standards in data collection, and lack of data sharing is high, and machine learning and artificial intelligence and advanced algorithm design have moved so fast, but the collection of well-tagged, meaningful agricultural data is way behind.

Regional Analysis For Artificial Intelligence in Agriculture Market:

North America (The United States, Canada, and Mexico)
Europe (Germany, France, UK, Russia, and Italy)
Asia-Pacific (China, Japan, Korea, India, and Southeast Asia)
South America (Brazil, Argentina, Colombia, etc.)
The Middle East and Africa (Saudi Arabia, UAE, Egypt, Nigeria, and South Africa)

Market Key Trends:

Labor Shortage and Increasing Costs of Labor to Drive the Artificial Intelligence Market
Across the world, a huge decline of the workforce is observed due to many reasons, like the lack of skilled labor, aging of farmers, and young farmers finding farming an unattractive profession, thus encouraging trends for automated farming operations. According to the International Labor Organization(ILO), agricultural labors in the percentage of the workforce declined from 81% to 48.2% in developing countries. Also, developed countries are not an exception in such a huge decline. Asia-Pacific, where agriculture occupies a major part of the economy, has a huge decline in workforce, which was nearly about 9% from 2015 to 2017. In Japan, the number of people working in farms witnessed a steep fall to 1.7 million in the year 2015, a 15% decline from the previous year.
The European agriculture sector has also faced such a huge decline in the workforce, which is nearly accounting to 12.8% for the corresponding period. The trend of decline in the agricultural workforce is encouraging government and private organizations to focus on automation operations by adopting artificial intelligence technologies in the agriculture sector. Owing to the above factors, the market for artificial intelligence in the agricultural sector is likely to boom in the years to come.

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What are the market factors that are explained in the report?

-Key Strategic Developments: The study also includes the key strategic developments of the market, comprising R&D, new product launch, M&A, agreements, collaborations, partnerships, joint ventures, and regional growth of the leading competitors operating in the market on a global and regional scale.

-Key Market Features: The report evaluated key market features, including revenue, price, capacity, capacity utilization rate, gross, production, production rate, consumption, import/export, supply/demand, cost, market share, CAGR, and gross margin. In addition, the study offers a comprehensive study of the key market dynamics and their latest trends, along with pertinent market segments and sub-segments.

-Analytical Tools: The Global Artificial Intelligence in Agriculture Market report includes the accurately studied and assessed data of the key industry players and their scope in the market by means of a number of analytical tools. The analytical tools such as Porter’s five forces analysis, SWOT analysis, feasibility study, and investment return analysis have been used to analyze the growth of the key players operating in the market.

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