Artificial Intelligence (AI) in Agriculture – Thematic Intelligence
All the vital news, analysis, and commentary curated by our industry experts.
Explore trends and insights from the following data in our ‘Artificial Intelligence (AI) in Agriculture’ thematic report:
- The report provides a detailed analysis of key challenges for the agriculture industry including climate change, geopolitics, disease, pressure on limited resources, environmental degradation, and much more.
- It offers forecasts for 2030 for the AI market, split into its key platforms and services.
- The report offers reviews of the segments of the AI value chain to invest, explore, or ignore, for agriculture players.
- The AI in agriculture timeline.
- The leading adopters of AI in the agriculture sector, the top specialist vendors for AI in the agriculture sector, and cross-sector AI vendors.
How is the ‘Artificial Intelligence in Agriculture’ thematic report different from other reports in the market?
- Position yourself for success by understanding how AI can help to solve the major challenges for the agriculture industry.
- Identify the leading and specialist vendors of AI solutions for the agriculture industry.
- Discover what each vendor offers and who some of their existing clients are.
- Quickly identify attractive investment targets in the agriculture industry by understanding which companies are most likely to be winners in the future based on our thematic scorecard.
- Gain a competitive advantage in the agriculture industry over your competitors by understanding the potential of AI solutions in the future.
We recommend this valuable source of information to anyone involved in:
- Entire Agriculture Value Chain
- Specialist AI Vendors in Agriculture
- Leading AI Adopters in Agriculture
- Technology Leaders and Startups
- Government and Research Organisations
- Professional Services – Investment Banks, PE/VC firms
- M&A/Investment, Management Consultants, and Consulting Firms
To Get a Snapshot of the Artificial Intelligence in Agriculture Thematic Report, Download a Free Report Sample
Ai In Agriculture Theme Analysis Report Overview
AI is vital to the fourth agricultural revolution, capable of human interaction, motion, and decision-making. This will help farmers deliver precision agriculture solutions. This category includes agricultural management techniques that observe, measure, and respond to crops’ inter- and intra-field variability for improved resource use and efficiency.
Precision agriculture requires a vast amount of data from onsite sensors and satellite imagery. This data can be quickly analyzed using AI. Ultimately, this will help farmers make good, timely decisions about their crop or livestock management. AI can further address the extreme variability inherent in the agricultural sector, exacerbated by climate change and geopolitical events. For example, it can be used to optimize farm planning, assess climate risks, handle disease management, and much more.
Furthermore, the impact of AI will expand across sectors and business functions as generative AI becomes more accurate and able to provide reliable factual advice.
The AI in agriculture thematic intelligence report provides an overview of this emerging technology and its wider impacts on commerce worldwide, while also providing insights on the immediate and future effects of AI in the agriculture markets.
|Value Chain||· Hardware
· Data Management
· Foundation AI
· Advanced AI Capabilities
|Leading AI Adopters in Agriculture||· AGCO
· John Deere
|Leading AI vendors||· Alibaba
· Alphabet (parent company of Google, Waymo, and DeepMind)
|Leading Specialist AI vendors in agriculture||· Apex.AI
· Stout Industrial Technology
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AI in Agriculture – Industry Analysis
According to GlobalData forecasts, the total artificial intelligence (AI) market was worth $81.3 billion in 2022 and is expected to grow at a CAGR of more than 35% from 2022-2030. For the agriculture sector, as traditional companies and farmers digitalize further, AI use will continue to grow. For example, to improve the efficiency of in-field operations, implement smart machinery for streamlined harvesting, deploy chatbots for distribution queries, and much more.
AI Market Revenue, by Platforms and Services, 2022-2030
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The AI in the agriculture industry analysis also covers:
- Mergers and acquisitions in all sectors
- Mergers and acquisitions in the agriculture sector
- Patent trends
- Company filing trends
- Hiring trends
AI - Value Chain Analysis
The AI value chain consists of hardware, data management, foundation AI, advanced AI capabilities, and delivery.
Data management: AI technology relies on large amounts of data, often called big data, and the various aspects of managing that data feature prominently in the AI value chain. However, data management is not exclusive to AI and can be seen as a generic foundational layer. Big data is produced by all forms of digital activity: phone calls, emails, sensors, payments, social media posts, and much more. It is also produced by machines, both hardware and software, in the form of machine-to-machine data exchanges. It is typically managed in data centers, either in the public cloud, corporate data centers, or end devices. Broadly speaking, the objective of data management is to secure the data (through data governance and security technology) and manage the data (by applying storage, processing, aggregation, and integration techniques).
AI Value Chain Analysis
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Artificial Intelligence in Agriculture - Competitive Landscape
Some of the leading adopters of AI:
- John Deere
Some of the leading AI Vendors:
- Alphabet (parent company of Google, Waymo, and DeepMind)
Some of the Specialist AI vendors in agriculture:
- Stout Industrial Technology
Buy Full Report to Know More About The Leading Vendors, Adopters, And Specialists in AI in Agriculture Sector, Download a Free Report Sample
Beijing Academy of Artificial Intelligence (Wu Dao)
Cloud Software Group
Hahn Group (Rethink Robotics)
Hyundai (Boston Dynamics)
Khronos Group (OpenCL)
Stout Industrial Technology
World Wide Web Consortium (Semantic Web)
Table of Contents
- 1. Executive Summary
- 2. Players
- 3. Agriculture Challenges
- 3.1. The Green Revolution’s second act
- 4. The Impact of AI on the Agriculture Sector
- 5. Case Studies
- 6. AI Timeline
- 7. Market Size and Growth Forecasts
- 8. Signals
- 8.1. Mergers and acquisitions – all sectors
- 8.2. Mergers and acquisitions in the agriculture sector
- 8.3. Patent trends
- 8.4. Company filings trends
- 8.5. Hiring trends
- 9. AI Value Chain
- 9.1. Hardware
- 9.2. Data management
- 9.3. Foundational AI
- 9.4. Advanced AI capabilities
- 9.5. Delivery
- 10. Companies
- 11. Glossary
- 12. Further Reading
- 13. Our Thematic Research Methodology
- 14. About GlobalData
- 15. Contact Us
Frequently asked questions
What are the components of the AI value chain?
The AI value chain consists of hardware, data management, foundation AI, advanced AI capabilities, and delivery.
Who are the leading adopters of the AI theme?
Some of the leading adopters of AI are AGCO, Bayer, and John Deere among others.
Who are the leading vendors in the AI theme?
Some of the leading vendors of AI are Alibaba, Alphabet (parent company of Google, Waymo, and DeepMind), and Amazon among others.
Who are the Specialist AI vendors in agriculture?
Some of the Specialist AI vendors in agriculture are Apex.AI, Stout Industrial Technology, and Persistent among others.
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