In recent years, there has been an increase in the adoption of artificial intelligence (AI) in agriculture. Farmers are using AI to improve crop yields, reduce costs, and make farming more efficient. The use of AI in agriculture is not new, but the technology is becoming more sophisticated and accessible. There are many different ways that farmers are using AI, including precision farming, machine learning, and robotics.
The global artificial Intelligence in agriculture Market was worth USD 1.26 billion in 2021. It is expected to grow at a 24.2% CAGR between 2023 and 2032. The major drivers for the market are increasing demand for labor, climate changes, and need for precision farming.
Artificial intelligence techniques in agriculture can increase yield and productivity. Agribusiness companies adopt artificial intelligence technologies that are predictive analytics-based. AI-based techniques and applications can be used to control pests, increase yields, monitor soil conditions, and improve agricultural-related tasks throughout the food supply chain. Because it analyzes farm data, artificial intelligence is being increasingly used in agriculture to improve harvest quality and accuracy.
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According to the UN, the global population will reach 9.8 billion people by 2050. The need to bring AI into the agriculture industry is driven by a rapidly growing population. A limited supply of arable land and the need to increase food production for food safety drive the need to create a green revolution using artificial intelligence, Internet of Things and big data. AI-enabled apps are used in many areas of the agriculture industry. These include predictive and recommendation analytics, identification and detection of pest infestations and soil monitoring.
Automation in agriculture also helps to allocate resources like fertilizers and water, determine optimal dates for crop sowing, detect weeds, and drive the demand for artificial intelligence solutions. The system can also recommend the number of seeds to be sow by using long-term weather data, commodity pricing predictions and production data. Many tech companies and start-ups are embracing the multiple benefits of AI-based applications to increase their IoT-enabled devices that can be used for large-scale deployments of AI applications in agriculture.
The use of artificial intelligence (AI) in agriculture is becoming more prevalent as growers seek out new ways to improve operational efficiency and optimize returns. While some applications are still in early stages of development and adoption, others such as automated machine learning and precision agriculture are seeing rapid uptake across the globe.
As the cost of AI hardware and software continues to fall, we can expect to see even more widespread adoption of these technologies in the agricultural sector in the years ahead.
Report Metric
Base Year – 2021
Historical Data – 2016-2021
Forecast Data – 2022-2031
Short-Term Projection Year – 2028
Projected Year- 2023
Long-Term Projected Year – 2023
Regional Scope – North America, Europe, Asian Pacific, Latin America, Middle East and Africa, and ROW
Company profiles
IBM Corporation
Microsoft
Deere & Company
AgEagle Aerial Systems Inc.
The Climate Corporation
Granular, Inc.
Descartes Labs, Inc.
Prospera Technologies
aWhere Inc.
Tule Technologies Inc.
Other Key Players
Market Segments Evaluated in the Report:
By Component
Service
Hardware
Software
By Technology
Predictive Analytics
Computer Vision
Machine Learning & Deep Learning
By Application
Livestock Monitoring
Drone Analytics
Agriculture Robots
Precision Farming
Other Applications
Key regions divided during this report:
– The Middle East and Africa Artificial Intelligence In Agriculture Market (Saudi Arabia, United Arab Emirates, Egypt, Nigeria, South Africa)
– North America Artificial Intelligence In Agriculture Market (United States, Canada, Mexico)
– Asia Pacific Artificial Intelligence In Agriculture Market (China, Korea, India, Southeast Asia)
– South America Artificial Intelligence In Agriculture Market (Brazil, Argentina, Colombia)
– Europe Artificial Intelligence In Agriculture Market (Germany, UK, France, Russia, Italy)
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The Report Covers
– Market value data analysis of 2021 and projections time to 2032.
– Each market segment’s annualized market revenue ($ million).
– A country-by-country analysis of the major geographic regions.
– Companies that are active in the global Artificial Intelligence in Agriculture industry. This report contains data on new product launches as well as relevant news.
– Analysis of business strategies by identifying the key market segments positioned for strong growth in the future.
– Market entry and expansion strategies analysis.
– Competitive strategies by identifying ‘who-stands-where’ in the market.
Key Questions answered in the Artificial Intelligence In Agriculture Market Report are:
How does the global Artificial Intelligence In Agriculture Market look like in 2021?
How many companies are currently involved in Artificial Intelligence In Agriculture development? Which are the most active in the pipeline?
What is the size of the global Artificial Intelligence In Agriculture market?
Which product segment grabbed the largest share in the Artificial Intelligence In Agriculture market?
How much revenue will promising Artificial Intelligence In Agriculture in the market, and in development, record to 2032?
How is the competitive scenario of artificial intelligence in the Agriculture market?
Which are the key factors aiding the Artificial Intelligence In Agriculture market growth?
Which region holds the maximum share in artificial intelligence in the Agriculture market?
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