AI in Precision Agriculture Market Trends and Forecast for Sustainable Farming Practices by 2031

InsightAce Analytic Pvt. Ltd. announces the release of a market assessment report on the "Global AI in Precision Agriculture Market- (By Type (Machine Learning, Computer Vision, Natural Language Processing, Predictive Analytics, Remote Sensing) By Application (Crop Monitoring, Yield Prediction, Soil Analysis, Irrigation Management, Pest and Disease Detection, Livestock Monitoring) By Component; By End-user, By Region, Trends, Industry Competition Analysis, Revenue and Forecast To 2031."

According to the latest research by InsightAce Analytic, the Global AI in Precision Agriculture Market is valued at US$ 7.2 Bn in 2023, and it is expected to reach US$ 20.9 Bn by 2031, with a CAGR of 14.7% during the forecast period of 2024-2031.

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AI in precision agriculture represents an innovative approach to farming that leverages advanced technologies to optimize multiple facets of crop production. By incorporating AI, GPS, and data analytics, precision agriculture seeks to revolutionize farming practices by improving crop yields, conserving resources, and addressing environmental challenges. This methodology utilizes real-time data on soil conditions, climate, and crop health, enabling farmers to make data-driven decisions that enhance productivity, reduce operational costs, and foster sustainability. The agricultural sector is experiencing significant technological advancements, with the increasing adoption of smart machines and intelligent robotics. Powered by AI, deep learning (DL), machine learning (ML), and data analytics, these innovations are positioned to drive the next phase of agricultural progress. This transformation has the potential to trigger a new green revolution, ensuring a reliable and sustainable food supply in the face of unpredictable environmental variables. AI and Big Data analytics offer promising solutions to global agricultural challenges, enhancing the efficiency and sustainability of farming practices.

List of Prominent Players in the AI in Precision Agriculture Market:
• IBM Corporation
• Microsoft Corporation
• John Deere
• Monsanto Company
• Syngenta AG
• Trimble Inc.
• Deere & Company
• AGCO Corporation
• Climate Corporation
• Descartes Labs
• Granular Inc.
• Prospera Technologies Ltd.
• Taranis
• Blue River Technology
• PrecisionHawk
• Farmwise
• Gamaya
• The Climate Corporation
• Ceres Imaging
• Awhere Inc.
• Tule Technologies
• AgEagle Aerial Systems Inc.
• Harvest Croo Robotics
• CNH Industrial N.V.
• Others

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Market Dynamics:
Drivers:
The increasing global demand for food, coupled with the need to optimize crop yields and resource efficiency, serves as a major catalyst for the adoption of AI in precision agriculture. AI technologies, including machine learning and predictive analytics, facilitate better decision-making, enabling precise irrigation, fertilization, and pest management. Moreover, advancements in Internet of Things (IoT) devices and sensors have enhanced real-time data collection and monitoring, further improving farm management practices. Government support, including initiatives and subsidies promoting smart farming techniques, is also fueling market growth. Additionally, growing awareness of sustainable farming practices and the environmental advantages of precision agriculture is accelerating the adoption of these technologies. The declining costs of AI technologies and increased investments in agricultural technology startups are further contributing to the market's expansion.

Challenges:
Despite the numerous benefits, the AI in precision agriculture market faces several challenges. High initial investment costs and the complexity of integrating AI solutions often deter small and medium-sized farms from adopting these technologies. Concerns over data privacy and security arising from the extensive data collection necessary for AI systems present significant risks. Additionally, the lack of standardized protocols and challenges surrounding the interoperability of various AI systems and agricultural equipment pose barriers to widespread adoption. The limited technical expertise among farmers further complicates the implementation and use of AI tools. Inconsistent internet connectivity in rural areas also impedes the seamless deployment of AI solutions. Furthermore, regulatory and compliance challenges regarding data usage and technology standards add complexity to the adoption process.

Regional Trends:
North America is projected to dominate the AI in precision agriculture market in terms of revenue, with expectations for substantial growth in the near future. The region's advanced technological infrastructure and the growing adoption of AI-driven solutions to enhance crop productivity and operational efficiency are key drivers of this expansion. Increased investments in smart farming technologies and supportive government initiatives are also contributing to the market's growth. In Europe, the market has experienced considerable growth, driven by the region's strong agricultural infrastructure, significant investments in AI technologies, and favorable governmental policies. The integration of AI tools for crop monitoring, yield prediction, and soil management has led to improvements in both agricultural productivity and sustainability across the region.

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Recent Developments:
• In May 2022, Alliance for a Green Revolution in Africa (AGRA) and Microsoft announced the expansion of their partnership to advance digital agriculture transformation in Africa to improve food security. The partnership of AGRA with Microsoft will support governments, farmers, and small and medium-sized enterprises (SMEs) to build food systems in the region by using digital tools provided by Microsoft.
• In February 2022, Farmers Edge and Deere & Company (US), a manufacturer of agriculture machinery and heavy equipment, entered into an agreement allowing users of Farm Command to integrate their data with the John Deer Operations Center account. This will give users the insights to make decisions that drive yields and profits.

Segmentation of AI in Precision Agriculture Market
AI in Precision Agriculture Market- By Type
• Machine Learning
• Computer Vision
• Natural Language Processing
• Predictive Analytics
• Remote Sensing
AI in Precision Agriculture Market- By Application
• Crop Monitoring Yield Prediction Soil Analysis
• Irrigation Management
• Pest and Disease Detection
• Livestock Monitoring
AI in Precision Agriculture Market- By Component
• Hardware
• Software
• Services
AI in Precision Agriculture Market- By End User
• Farmers/Growers
• Agricultural Cooperatives
• Agricultural Consultants
• Research and Educational Institutes
• Government Bodies
AI in Precision Agriculture Market- By Region
North America-
• The US
• Canada
• Mexico
Europe-
• Germany
• The UK
• France
• Italy
• Spain
• Rest of Europe
Asia-Pacific-
• China
• Japan
• India
• South Korea
• South East Asia
• Rest of Asia Pacific
Latin America-
• Brazil
• Argentina
• Rest of Latin America
Middle East & Africa-
• GCC Countries
• South Africa
• Rest of Middle East and Africa

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This release was published on openPR.