Dublin, Sept. 30, 2025 (GLOBE NEWSWIRE) -- The "Generative AI In Agriculture Market Size, Share & Trends Analysis Report By Technology, By Application (Precision Farming, Livestock Management, Agricultural Robotics & Automation, Weather Forecasting), By Region, And Segment Forecasts, 2025 - 2033" has been added to ResearchAndMarkets.com's offering.
The global market for generative AI in agriculture, projected to skyrocket from USD 226.2 million in 2024 to an impressive USD 2.15 billion by 2033, is anticipated to grow at a robust CAGR of 28.7% from 2025 onwards.
With increasing adoption of generative AI models, farmers are empowered to make informed decisions regarding yields, weather impacts, and input requirements, reinforcing the principles of precision agriculture through effective scenario-based planning. Guided by the advent of specialized AI models, the industry is evolving toward AI-driven crop simulations and decision-making tools.
The rise of specialized, efficient AI solutions, such as those developed by Cropin Technology Solutions with their launch of akshara, an open-source micro language model tailored for the Global South, mirrors the increasing demand for localized, multilingual advisories that bolster climate resilience. The trend indicates a shift from generalized AI applications to scalable, frugal solutions designed for underserved agricultural ecosystems, significantly benefiting smallholder farmers in emerging regions.
Enhanced integration of AI with existing digital agriculture platforms facilitates timely, data-driven decision making throughout diverse agricultural cycles. By incorporating satellite imagery, IoT data, and advanced management systems, these platforms deliver specific, practical recommendations that optimize resource efficiency, support better crop outcomes, and mitigate operational risks. Collaborations like that of Bayer AG with Microsoft and Ernst & Young, launching a generative AI system supported by proprietary agronomic data, underscore the momentum toward intelligent, connected farming solutions.
Technological advancements in machine learning, computer vision, and cloud infrastructure play a pivotal role in modernizing agricultural practices. Predictive machine learning algorithms streamline insights into crop yields and soil health, while computer vision processes utilize drone and satellite technology for real-time crop monitoring. Improved cloud infrastructure supports scalable data management, enabling remote access to analytics that enhances decision-making. IoT devices further contribute to seamless integration, improving operational efficiency across the board and encouraging collaborative engagement across stakeholders.
Global Generative AI In Agriculture Market Report Segmentation
This comprehensive report evaluates market trajectory at global, regional, and country levels, analyzing contemporary trends and opportunities within various sub-segments.
Why You Should Buy This Report?
- Comprehensive Market Analysis
- Competitive Landscape Overview
- Future Trend Insights and Drivers
- Actionable Strategic Recommendations
Report Coverage Includes:
- Market intelligence for informed decision-making
- Revenue forecasts up to 2033
- Growth opportunities and trend analyses
- Segment and regional revenue forecasts
- Competition strategy and market shares
- Product innovation insights
Companies Featured
- Agmatix
- AgroScout
- Bayer AG
- Carbon Robotics
- Deere & Company (John Deere)
- DeepAgro
- IBM Corporation
- KissanAI
- Microsoft
- Syngenta Group
Key Attributes:
| Report Attribute | Details |
| No. of Pages | 200 |
| Forecast Period | 2024 - 2033 |
| Estimated Market Value (USD) in 2024 | $0.23 Billion |
| Forecasted Market Value (USD) by 2033 | $2.15 Billion |
| Compound Annual Growth Rate | 28.7% |
| Regions Covered | Global |
Key Topics Covered:
Chapter 1. Methodology and Scope
- 1.1. Market Segmentation & Scope
- 1.2. Market Definition
- 1.3. Information Procurement
- 1.4. Information Analysis
- 1.5. Market Formulation & Data Visualization
- 1.6. Data Validation & Publishing
Chapter 2. Executive Summary
- 2.1. Market Insights
- 2.2. Segmental Outlook
- 2.3. Competitive Outlook
Chapter 3. Generative AI in Agriculture Market Variables, Trends & Scope
- 3.1. Global Generative AI in Agriculture Market Outlook
- 3.2. Industry Value Chain Analysis
- 3.3. Market Dynamics
- 3.4. Porter's Five Forces Analysis
- 3.5. PESTEL Analysis
Chapter 4. Generative AI in Agriculture Market: Technology Estimates & Forecasts
Chapter 5. Generative AI in Agriculture Market: Application Estimates & Forecasts
Chapter 6. Generative AI in Agriculture Market: Regional Estimates & Trend Analysis
Chapter 7. Competitive Landscape
- 7.1. Recent Developments & Impact Analysis, By Key Market Participants
- 7.2. Vendor Landscape
- 7.3. Competitive Dynamics
- 7.4. Company Profiles
For more information about this report visit https://www.researchandmarkets.com/r/2872pu
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