IMARC Group, a leading market research company, has recently releases report titled “AI in Agriculture Market: Global Industry Trends, Share, Size, Growth, Opportunity and Forecast 2024-2032” offers a comprehensive analysis of the industry, which comprises insights on the AI in agriculture industry growth. The global market size reached US$ 1.8 Billion in 2023. Looking forward, IMARC Group expects the market to reach US$ 10.1 Billion by 2032, exhibiting a growth rate (CAGR) of 20.51% during 2024-2032.

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Factors Affecting the Growth of the AI in Agriculture Industry:

• Enhanced Crop Yield and Monitoring:

The increasing demand for enhanced crop yield and more efficient monitoring systems represents one of the crucial factors impelling the market growth. The rising need to maximize agricultural productivity to meet food demands is encouraging the adoption of AI technologies, including machine learning (ML) and predictive analytics, to analyze farm data, enabling farmers to make more informed decisions. These technologies help in predicting the optimal planting seasons, understanding soil health, and managing pests and diseases more effectively. These AI-driven solutions also assist in real-time monitoring of crop growth, ensuring that issues are identified and addressed promptly, thereby significantly improving yield and quality.

• Integration of Big Data:

The integration of big data analytics in agriculture is another major driver. The vast amount of data generated from various sources like satellite imagery, soil sensors, weather stations, and drones provide valuable insights for farmers, and AI algorithms analyze this data to provide actionable insights on crop health, soil conditions, moisture levels, and weather predictions. This helps in optimizing agricultural practices, reducing resource waste, and increasing crop productivity. This incorporation also enables predictive analytics for better planning and risk management, thus making farming more sustainable and efficient in the face of climate change and other environmental challenges.

• Adoption of Precision Agriculture:

The growing adoption of precision agriculture, which involves the use of AI and the internet of things (IoT) technologies to enable more precise and controlled farming practices, is positively influencing the market. This includes the use of sensors, global positioning systems (GPS), and AI-driven decision support systems to optimize field-level management regarding crop farming. This method maximizes yields while minimizing environmental impact by tailoring farming practices based on specific conditions of each part of the field. It enables farmers to apply the right amount of inputs like water, fertilizers, and pesticides at the right time and place, thereby reducing costs and increasing sustainability. The efficiency and cost-effectiveness of precision agriculture are major factors contributing to its increased adoption globally.

Top Companies Operating in Global AI in Agriculture Industry:

• A.A.A Taranis Visual Ltd.
• Ag Leader Technology
• AgEagle Aerial Systems Inc.
• Bayer AG
• Deere & Company
• Gamaya
• Granular Inc. (DuPont de Nemours, Inc.)
• International Business Machines Corporation
• Raven Industries Inc
• Trimble Inc.
• Oracle Corporation and Wipro Limited.

AI in Agriculture Market Report Segmentation:

By Offering:

• Software
• Hardware
• AI-as-a-Service
• Services

Software represents the largest segment due to the increasing adoption of AI-powered software solutions for crop management and yield optimization.

By Technology:

• Machine Learning
• Computer Vision
• Predictive Analytics

Machine learning accounts for the biggest segment as it enables advanced data analysis and predictive modeling for precision agriculture.

By Application:

• Precision Farming
• Agriculture Robots
• Livestock Monitoring
• Drone Analytics
• Labor Management
• Others

Precision Farming exhibits clear dominance as it offers farmers enhanced control over crop production and resource utilization.

Regional Insights:

• North America (United States, Canada)
• Asia Pacific (China, Japan, India, South Korea, Australia, Indonesia, Others)
• Europe (Germany, France, United Kingdom, Italy, Spain, Russia, Others)
• Latin America (Brazil, Mexico, Others)
• Middle East and Africa

North America dominates the market due to the early adoption of AI in agriculture, well-established agricultural infrastructure, and robust investment in technological advancements within the sector.

Global AI in Agriculture Market Trends:

The increasing employment of autonomous robots in farming operations for performing a wide range of tasks, such as harvesting, weeding, and planting, with precision and efficiency is supporting the market growth. The adoption of automation robots is also driven by the need to reduce labor costs and increase operational efficiency. These robots not only work faster than human laborers but also with greater accuracy, reducing waste and improving yield quality.

Furthermore, the growing integration of blockchain technology in agricultural operations is enhancing traceability and transparency in the agricultural supply chain. This technology provides a secure and immutable ledger for recording transactions, which is crucial for tracking the journey of agricultural products from farm to table. It ensures the authenticity of organic and sustainably farmed produce, thereby building trust among consumers.

Other Key Points Covered in the Report:

• COVID-19 Impact
• Porters Five Forces Analysis
• Value Chain Analysis
• Strategic Recommendations

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