Global Artificial Intelligence in Agriculture Market 2023: Increased Farmland Consolidation and Large Farm Size Fuels the Sector

DUBLIN, April 27, 2023 /PRNewswire/ -- The "Artificial Intelligence in Agriculture Market - A Global and Regional Analysis: Focus on Product, Application, Supply Chain Analysis, and Country Analysis - Analysis and Forecast, 2022-2027" report has been added to  ResearchAndMarkets.com's offering.

The global artificial intelligence in agriculture market was valued at $1,517.0 million in 2022 and is expected to reach $4,096.1 million in 2027, following a CAGR of 21.98% during 2022-2027.

Owing to the growing demand for food and grains, the growth in the artificial intelligence in agriculture market is expected to be driven by the increasing adoption of digital and smart agriculture equipment and technologies.

Market Lifecycle Stage

The artificial intelligence in agriculture market is in a growing phase. Immense corporate investments and research and development activities are underway to develop artificial intelligence in agriculture, which are expected to increase due to the growing need for agriculture optimization backed by the incorporation of emerging technologies.

New entrants are penetrating the market backed up by government funding and corporate investments, which is one of the major opportunities in the global artificial intelligence in agriculture market. Moreover, artificial intelligence in agriculture also help in enhancing yield quality due to the timely detection of pest infestation and diseases. Artificial intelligence in agriculture also facilitates the safe and quality harvesting and picking of harvests, thus preventing crop losses and damages.

Impact

• With an increased worldwide demand for improved qualities of foods and grains, the shift to digital, smart, and data-driven equipment in the agriculture sector brings significant sales and financing opportunities. The shift is more prominent in regions such as Europe and North America.
• Furthermore, artificial intelligence in agriculture has a moderate to high impact on pest detection and crop scouting operations through timely and efficient detection of pests and diseases at the plant level.

Impact of Ukraine-Russia Crisis

The market for technologies in the agriculture sector, including AI-enabled, is facing a negative impact due to Ukraine-Russia tensions. The two countries are blessed with extensive technological and agricultural benefits. The tensions are leading the AI-technology providers and start-ups to reach out to markets other than the two countries.

Many start-ups in the global artificial intelligence in agriculture market have staged their pilot projects in Ukraine and Russia before commercially launching their products. Similarly, many companies find Ukraine and Russia suitable for agricultural technology testing and trials owing to the presence of different varieties of crops and high adoption rates among farmers.

Recent Developments in the Global Artificial Intelligence in Agriculture Market

• In May 2021, Robert Bosch GmBH unveiled its new Artificial Intelligence based IoT platform to keep real time track of energy consumption, electrical parameters in healthcare, agriculture, and other sectors.
• In February 2019, Ceres Imaging developed and launched its Center-Pivot Analytics Suite, a full-service imagery solution designed specifically for center-pivot irrigated row crops.
• In February 2022, Plantix expanded its market presence in the Asia-Pacific region by launching its product, Plantix Vision API in Bangladesh.
• In February 2021, Microsoft Corporation launched its business expansion in Indonesia to support agricultural sector there in.
• In May 2021, Valmont Industries acquired Prospera Industries for $300 million to establish greater returns for mutual customer farmers.
• In February 2021, DeHaat acquired Farm Guide, a data science start-up to further enhance its advisory and market services.
• In December 2021, Connecterra B.V. collaborated with Lely. With this collaboration, Lely aimed to use Connecterra B.V.'s advancements in machine learning and artificial intelligence to provide more insights to farmers. Also, the technologies aid in integrating farm technologies with sensors enabled with artificial intelligence for developing farm management systems.
• In May 2022, Taranis expanded its partnership with DJI and DroneNerds.com in the United States. To make more intelligent data-driven decisions, the collaboration will take advantage of cutting-edge AI and drone technologies.

Demand - Drivers and Limitations

The following are the demand drivers for the global artificial intelligence in agriculture market:

• Surging Need for Automation in Agriculture
• Increased Farmland Consolidation and Large Farm Size

The market is expected to face some limitations as well due to the following challenges:

• Data Ownership and Privacy Concerns
• Technical Constraints of Implementation and Maintenance

How can this report add value to end users?

Product/Innovation Strategy: The product segment helps the reader understand the different types of artificial intelligence modes of deployment and product types available for deployment in the agriculture sector and their potential globally.

Growth/Marketing Strategy: The artificial intelligence in agriculture market has seen major development by key players operating in the market, such as business expansion, partnership, collaboration, and joint venture. The favoured strategy for the companies has been product partnerships, joint ventures, and product launches to strengthen their position in the global artificial intelligence in agriculture market. For instance, in February 2019, CNH Industrial N.V. launched an Advanced Farming Systems (AFS) Connect platform for farm, fleet, and data management.

Competitive Strategy: Key players in the artificial intelligence in agriculture market analyzed and profiled in the study involve artificial intelligence in agriculture manufacturers. Moreover, a detailed competitive benchmarking of the players operating in the artificial intelligence in agriculture market has been done to help the reader understand how players stack against each other, presenting a clear market landscape. Additionally, comprehensive competitive strategies such as partnerships, agreements, and collaborations will aid the reader in understanding the untapped revenue pockets in the market.

Key Market Players and Competition Synopsis

The companies that are profiled have been selected based on inputs gathered from primary experts and analysing company coverage, product portfolio, and market penetration.

Some manufacturing companies with a global presence include Microsoft Corporation, Climate LLC, CNH Industrial N.V., Deere & Company, and IBM Corporation among others. Collectively these companies account for approximately 42.90% of the total global artificial intelligence in agriculture market. Other 57.10% of the market share is dominated by Aquabyte, Ceres Imaging, Taranis, and CropIn Technology Solutions Pvt Ltd. among others.

Key Companies Profiled

• Alibaba Group Holding Limited
• Aquabyte
• Ceres Imaging
• Climate LLC
• CNH Industrial N.V.
• Connecterra B.V.
• CropIn Technology Solutions
• Deere & Company
• DJI
• Granular Inc.
• IBM Corporation
• Microsoft Corporation
• PrecisionHawk, Inc.
• Plantix
• XPERTSEA
• Agrible
• Prospera Technologies
• Taranis
• UMITRON
• Wolkus Technology Solutions Private Limited (Fasal)

Key Attributes:

Key Topics Covered:

1 Markets
1.1 Industry Outlook
1.1.1 Market Definition
1.1.2 Ecosystem/Ongoing Programs
1.1.2.1 Consortiums and Associations
1.1.2.2 Regulatory Bodies
1.1.2.3 Government Initiatives
1.2 Business Dynamics
1.2.1 Business Drivers
1.2.1.1 Surging Need for Automation in Agriculture
1.2.1.1.1 Implementation of Advanced Technologies in Agriculture
1.2.1.1.2 Need to Increase Field Productivity
1.2.1.1.3 Aging Workforce
1.2.1.1.4 Increasing Labor Prices
1.2.1.2 Increased Farmland Consolidation and Large Farm Size
1.2.2 Business Challenges
1.2.2.1 Data Ownership and Privacy Concerns
1.2.2.1.1 Lack of Standardization
1.2.2.2 Technical Constraints of Implementation and Maintenance
1.2.3 Market Strategies and Developments
1.2.3.1 Product Developments
1.2.3.2 Business Developments
1.2.4 Corporate Strategies
1.2.4.1 Mergers and Acquisitions
1.2.4.2 Partnerships, Collaborations, and Joint Ventures
1.2.5 Investments
1.2.5.1 Snapshot of Corporate Strategies Adopted by the key Players in the Market
1.2.6 Business Opportunities
1.2.6.1 Government Initiatives to Promote Digital Agriculture
1.2.6.2 Emerging Complexities in Data-Driven Farming
1.2.6.3 Variable-Rate Technology through AI
1.2.7 Case Study
1.2.7.1 Ceres Imaging in Data Analytics
1.2.7.2 CropIn Technology Solutions in Yield Optimization
1.2.7.3 Connecterra B.V. in Livestock Monitoring
1.2.7.4 Aquabyte in Aquaculture Management
1.3 Investment Landscape
1.4 Impact of Ukraine-Russia Crisis on the Global Artificial Intelligence in Agriculture Market

2 Application
2.1 Global Artificial Intelligence in Agriculture Market (by Application)
2.1.1 Yield Optimization
2.1.1.1 AI for Pest and Disease Detection
2.1.1.2 AI for Yield Prediction
2.1.1.3 AI for Space and Resource Utilization
2.1.2 Data Analytics
2.1.3 Livestock Monitoring
2.1.4 Aquaculture Management
2.2 Demand Analysis of the Global Artificial Intelligence in Agriculture Market (by Application)

3 Products
3.1 Global Artificial Intelligence in Agriculture Market (by Product)
3.1.1 Global Artificial Intelligence in Agriculture Market (by Mode of Deployment)
3.1.1.1 On-Cloud Deployment
3.1.1.2 On-Premises Deployment
3.1.1.3 Edge Deployment
3.1.1.4 Hybrid Deployment
3.1.2 Global Artificial Intelligence in Agriculture Market (by Product Type)
3.1.2.1 Application Programming Interface (API)
3.1.2.2 User Interface (UI)
3.2 Demand Analysis of the Global Artificial Intelligence in Agriculture Market (by Product)
3.2.1 Demand Analysis of the Global Artificial Intelligence in Agriculture Market (by Mode of Deployment)
3.2.2 Demand Analysis of the Global Artificial Intelligence in Agriculture Market (by Product Type)
3.3 Supply Chain Analysis
3.4 Patent Analysis
3.4.1 Patent Analysis (by Status)
3.4.2 Patent Analysis (by Inventor Type)
3.4.3 Patents Analysis (by Patent Office)

4 Regions

5 Markets - Competitive Benchmarking & Company Profiles
5.1 Competitive Benchmarking
5.2 Market Share Analysis
5.2.1 Market Share Analysis for Global Artificial Intelligence in Agriculture Market
5.3 Company Profiles
5.4 Key Startups in the Artificial Intelligence in Agriculture Ecosystem

6 Research Methodology

For more information about this report visit https://www.researchandmarkets.com/r/9i0ead

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