Dublin, Aug. 26, 2024 (GLOBE NEWSWIRE) -- The "Artificial Intelligence in Agriculture Market - A Global and Regional Analysis: Focus on Application, Mode of Deployment, Product Type, and Region - Analysis and Forecast, 2024-2034" report has been added to ResearchAndMarkets.com's offering.
The global artificial intelligence in agriculture market was valued at $1.82 billion in 2023 and is expected to reach $12.47 billion by 2034, with a CAGR of 18.95% from 2024 to 2034
The market is in a growth phase and is projected to experience significant expansion. Market players investing in research, infrastructure development, and strategic partnerships are anticipated to capitalize on the increasing demand for artificial intelligence in agriculture, driven by advancements in technology and development in AI, over the forecast period from 2024 to 2034.
North America leads the market for artificial intelligence (AI) in agriculture due to a combination of technological advancements, strong infrastructure, and substantial investment. The region is home to some of the world's leading tech companies, research institutions, and startups focused on developing AI solutions. This rich ecosystem fosters innovation and the rapid adoption of AI technologies in farming. Additionally, North American farms often have access to capital and government support, allowing them to integrate advanced technologies such as AI more swiftly than those in many other regions.
The widespread adoption of AI in North American agriculture is also driven by the high demand for precision farming techniques aimed at boosting productivity and sustainability. Farmers in this region leverage AI to optimize everything from planting and irrigation to pest management and harvest schedules, improving yields and reducing environmental impacts. Moreover, the region's robust digital infrastructure supports seamless data collection and analysis, which is crucial for effective AI deployment. These factors collectively ensure North America's leading position in the global AI in agriculture market.
Introduction of Artificial Intelligence in Agriculture
Artificial intelligence (AI) in agriculture represents a transformative shift in how farming operations are conducted across the globe. By integrating advanced algorithms and machine learning models with traditional agricultural practices, AI enables a more precise and efficient approach to farming. This technology harnesses vast amounts of data from drones, satellites, ground sensors, and IoT devices to optimize crop yields, reduce waste, and increase efficiency.
AI applications in agriculture include predictive analytics for weather and crop health, automated equipment for planting and harvesting, and intelligent systems for pest and disease management. The adoption of AI in agriculture promises to enhance the productivity of farms, enable sustainable practices, and reshape the agricultural landscape by making it more data-driven and technologically equipped. This pivotal integration of AI not only caters to increasing global food demands but also addresses critical challenges such as resource conservation and climate change mitigation, making agriculture more adaptable and resilient for the future.
Market Segmentation:
Yield Optimization Segment to Dominate Global Artificial Intelligence in Agriculture Market (by Application)
Yield optimization is a dominant application of artificial intelligence (AI) in agriculture due to its direct impact on maximizing crop production and improving farm efficiency, which are critical to profitability and sustainability.
With the global population growing and urbanization reducing arable land, there is significant pressure to produce more food from less land. AI-driven yield optimization helps identify the best crop choices, planting patterns, and resource allocation to maximize output.
AI enables precision agriculture, which involves the precise application of water, fertilizers, and pesticides using data collected from drones, IoT devices, and sensors. This targeted approach not only improves yield but also reduces resource waste and environmental impact.
In essence, yield optimization through AI not only addresses the economic bottom line by maximizing output and reducing costs but also aligns with sustainable farming practices that are increasingly vital in a world facing environmental challenges. This dual benefit is why yield optimization is a leading application of AI in agriculture.
On-Cloud Deployment to Dominate Global Artificial Intelligence in Agriculture Market (by Mode of Deployment)
On-cloud deployment is gaining prominence in the AI-driven agriculture sector due to its scalability and flexibility. Cloud platforms allow farmers to adjust their AI resources as per seasonal demands or expansion needs without heavy upfront investments in infrastructure. This mode of deployment is not only cost-effective, minimizing the need for costly hardware and ongoing maintenance, but also caters to the financial realities of small- to mid-sized farms.
Furthermore, cloud services enhance AI applications in agriculture by integrating diverse data sources, such as satellite imagery and IoT sensors, which are essential for developing effective AI models. These platforms support advanced analytics for real-time decision-making, such as weather prediction or pest detection. They also offer automatic software updates, robust security measures, and data backup systems, ensuring that agricultural stakeholders can collaborate efficiently and manage operations remotely, securely, and without interruption.
How can this report add value to an organization?
Product/Innovation Strategy: The product segment helps the reader understand the different products of global artificial intelligence in agriculture based on their use in agribusiness companies, agricultural cooperatives, government and private research institutes, and others. The technology types include drone scouting, mobile scouting, satellite imagery, and other advanced methods. The market is poised for significant expansion with ongoing technological advancements, increased investments, and growing awareness of the importance of precision agriculture. Therefore, the digital soil mapping business is a high-investment and high-revenue generating model.
Growth/Marketing Strategy: The global artificial intelligence in agriculture market has been growing rapidly. The market offers enormous opportunities for both existing and emerging players. Strategies covered in this segment include mergers and acquisitions, product launches, partnerships, collaborations, business expansions, and investments. Companies primarily focus on product development to maintain and strengthen their market positions.
Competitive Strategy: Key players in the global artificial intelligence in agriculture market analyzed and profiled in the study include technology developers and solution providers. Additionally, a comprehensive competitive landscape, including partnerships, agreements, and collaborations, is expected to aid the reader in understanding the untapped revenue pockets in the market.
Key Market Players and Competition Synopsis
The companies that are profiled in the global artificial intelligence in agriculture market have been selected based on inputs gathered from primary experts and analyzing company coverage, product portfolio, and market penetration.
Key Attributes:
| Report Attribute | Details |
| No. of Pages | 140 |
| Forecast Period | 2024 - 2034 |
| Estimated Market Value (USD) in 2024 | $2.2 Billion |
| Forecasted Market Value (USD) by 2034 | $12.47 Billion |
| Compound Annual Growth Rate | 18.9% |
| Regions Covered | Global |
Market Dynamics Overview
Market Drivers
- Need for Innovation in Farming Practices
- Growing Adoption of AI Due to Enhanced Data Collection and Analysis
Trends: Current and Future Impact Assessment
- Adoption of AI-Driven Precision Agriculture
- Utilization of AI for Predictive Analytics in Farm Management
- Case Study: IBM Watson Decision Platform for Agriculture
Market Restraints
- Constraints in Land Availability and Farming Inputs
- Multifaceted Barriers to AI Adoption
Market Opportunities
- Addressing Labor Shortages with AI and Robotics
- Enhanced AI Accuracy with Expanded Datasets
Supply Chain Overview
- Value Chain Analysis
- Market Map
Research and Development Review
- Patent Filing Trend (by Number of Patents, Country)
Regulatory Landscape
Impact Analysis for Key Global Events
Competitive Benchmarking & Company Profiles
- Deere & Company
- IBM Corporation
- Microsoft Corporation
- Climate LLC
- Alibaba Group Holding Limited
- Aquabyte
- Ceres Imaging
- CNH Industrial N.V.
- Connecterra B.V.
- Cropin Technology Solutions Private Limited
- DJI
- Nedap Livestock Management
- Plantix
- Blue River Technology
- Farmers Edge
For more information about this report visit https://www.researchandmarkets.com/r/7znglt
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