Artificial Intelligence (AI) in Agriculture – Thematic Intelligence

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Published: July 06, 2023 Report Code: GDAGR-TR-S003-TH

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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.

Report Pages 66
Regions Covered Global
Value Chain ·       Hardware

·       Data Management

·       Foundation AI

·       Advanced AI Capabilities

·       Delivery
Leading AI Adopters in Agriculture ·       AGCO

·       Bayer

·       John Deere
Leading AI vendors ·       Alibaba

·       Alphabet (parent company of Google, Waymo, and DeepMind)

·       Amazon
Leading Specialist AI vendors in agriculture ·       Apex.AI

·       Stout Industrial Technology

·       Persistent
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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

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

AI Value Chain Analysis

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Artificial Intelligence in Agriculture - Competitive Landscape

Some of the leading adopters of AI:

  • AGCO
  • Bayer
  • John Deere

Some of the leading AI Vendors:

  • Alibaba
  • Alphabet (parent company of Google, Waymo, and DeepMind)
  • Amazon

Some of the Specialist AI vendors in agriculture:

  • AI
  • Stout Industrial Technology
  • Persistent

Buy Full Report to Know More About The Leading Vendors, Adopters, And Specialists in AI in Agriculture Sector, Download a Free Report Sample

Ab Initio
ABB
Advantech
AEye
AGCO
Algorithmia
Alibaba
Alphabet
Alteryx
Amazon
Ambarella
AMD
ANYbotics
Apex.AI
Apple
Aptiv
Ataccama
Attivio
Aurora
Autodesk
BAE Systems
Baidu
Basler
Bayer
Beijing Academy of Artificial Intelligence (Wu Dao)
BigML
BMC Software
Boomi
Brain Corp
C3.ai
Cambricon
Cargill
Celigo
Cerebras
Clarifai
Cloud Software Group
Cloudera
CloudWalk
CNH Industrial
Cognex
CognitiveScale
Cohesity
Continental
Couchbase
Cyclr
Data Virtuality
Dataiku
DataStax
DeepAI
Denso
Epic Games
Exasol
Facewatch
Festo
Fetch Robotics
GM (Cruise)
Gooey.AI
Graphcore
Groq
H2O.ai
Hahn Group (Rethink Robotics)
Hawk-Eye Innovations
HCL Technologies
Hikvision
Hitachi
Hive
Horizon Robotics
HPE
Huawei
Hugging Face
Hyundai (Boston Dynamics)
IBM
iFlytek
ImmersiveTouch
Infineon
Informatica
Intel
iRobot
Jasper Art
John Deere
Keras
Kernel
Keyence
Khronos Group (OpenCL)
Lockheed Martin
Lumentum
Luminar Technologies
Magna
MakeML
MarkLogic
MathWorks
Megvii (Face++)
Merative
Meta
Microsoft
Midea (KUKA)
Midjourney
Mindmaze
MindsEye
Mobileye
MongoDB
Nauto
NEC
Neurala
Neuralia
Neuralink
Neuroelectrics
NightCafe
Nippon Ceramic
Northop Grumman
Nutrien
Nvidia
Okta
Omron
OpenAI
OpenNN
Oracle
Palantir
Panasonic
Panoply
PayPal (Simility)
PEAT
Persistent
Pony.ai
Precisely
Profisee
Prophesee
Qualcomm
RapidMiner
Renesas
Restb.ai
Rockwell Automation
Rohm
ROS-Industrial
Samsung Electronics
SAP
SAS
SenseTime
Sherpa.ai
SiLC
Snowflake
Software AG
SoundHound
SparkCognition
Splunk
Stemmer Imaging
Stout Industrial Technology
StreamSets
Syngenta
Talend
TE Connectivity
Teledyne
Tencent
Teradata
Teradyne
Tesla
Texas Instruments
Toshiba
Tung Thih
Unity Technologies
Velodyne
Verdant Robotics
Veritas
Visteon
VoltDB
Voyant Photonics
Wolfram
Workato
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

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