Global AI in Agriculture Market to Reach $12.95 Billion by 2033: Key Trends and Growth Forecast

Market Size & Growth

• Market Size (2024): USD 2.18 Billion
• Projected Market Size (2033): USD 12.95 Billion
• Compound Annual Growth Rate (CAGR) (2025-2033): 19.48%

Key Market Drivers:

• Increasing Need for Precision Farming
• Rising Adoption of Agricultural Drones and Robotics
• Advancements in Machine Learning and Data Analytics

Emerging Trends

• Expansion of Smart Greenhouses
• Use of Natural Language Processing (NLP) in Advisory Systems
• Integration with Blockchain for Supply Chain Transparency

Segmentation Highlights

• Analysis By Offering
• Analysis By Technology
• Analysis By Application
• Regional Insights

Market Overview:

According to IMARC Group's latest research publication, the global AI in agriculture market size was valued at USD 2.18 Billion in 2024. Looking forward, IMARC Group estimates the market to reach USD 12.95 Billion by 2033, exhibiting a CAGR of 19.48% during 2025-2033.

This detailed analysis primarily encompasses industry size, business trends, market share, key growth factors, and regional forecasts. The report offers a comprehensive overview and integrates research findings, market assessments, and data from different sources. It also includes pivotal market dynamics like drivers and challenges, while also highlighting growth opportunities, financial insights, technological improvements, emerging trends, and innovations. Besides this, the report provides regional market evaluation, along with a competitive landscape analysis.

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Our report includes:

• Market Dynamics
• Market Trends and Market Outlook
• Competitive Analysis
• Industry Segmentation
• Strategic Recommendations

Growth Factors in the AI in Agriculture Industry:

• Increasing Need for Precision Farming

Farmers are increasingly turning to AI-enabled precision farming to meet rising productivity demands while coping with soil degradation, climate variability, and limited arable land. These systems leverage multisource data—from IoT sensors to weather satellites—to fine-tune irrigation, seeding, and fertilization schedules. In Brazil, AI-driven models now offer real-time alerts on rainfall patterns, enabling timely nutrient application and disease prevention. Similarly, variable-rate technology (VRT) powered by machine learning helps reduce fertilizer usage by over 20%, cutting input costs and boosting soil health. As global food security concerns rise, precision farming technologies are becoming indispensable for long-term agricultural sustainability.

• Rising Adoption of Agricultural Drones and Robotics

The deployment of drones and robotics in agriculture is accelerating as farms seek efficiency amid labor shortages and climate uncertainty. Equipped with AI, drones can now identify weed clusters, evaluate crop maturity, and generate prescription maps for targeted spraying. For instance, in Spain, vineyards use drones with thermal imaging to assess vine water stress, enhancing irrigation decisions. Meanwhile, robots are being deployed for autonomous seed planting, harvesting, and real-time field mapping. Companies like Agrobot and Blue River Technology are creating specialized AI robots tailored for high-value crops. This mechanized precision is not only reducing human error but also ensuring more sustainable use of inputs.

• Advancements in Machine Learning and Data Analytics

Machine learning is fueling a major shift from reactive to predictive farm management. Today’s AI systems continuously learn from environmental data, enabling farmers to anticipate crop diseases, optimize harvesting times, and plan resource allocation months in advance. In China, ML algorithms are helping rice farmers balance fertilizer applications across large plots based on satellite imagery. Decision platforms integrate soil, climate, and yield data to create dynamic risk maps, enhancing insurance and lending models. These tools are particularly valuable for smallholder farmers, offering access to insights previously available only to large agribusinesses. ML’s growing integration into agri-platforms is enhancing both productivity and resilience.

Key Trends in the AI in Agriculture Market:

• Expansion of Smart Greenhouses

AI-driven smart greenhouses are optimizing environmental controls with real-time feedback loops. Systems now regulate light spectra, temperature, and humidity based on plant growth models, achieving superior yields with minimal waste. In Canada, growers using AI-powered controls have reduced energy usage by 18% while boosting output. Smart sensors track microclimatic conditions and AI models interpret these signals to automate irrigation or trigger CO₂ enrichment. AI vision systems also detect pest outbreaks or fungal development before visible symptoms appear. This high-tech approach is enabling continuous cultivation cycles and better resource efficiency, making AI-integrated greenhouses vital for controlled-environment agriculture.

• Use of Natural Language Processing (NLP) in Advisory Systems

NLP is transforming agricultural advisory by making expert insights more accessible through voice, text, and chat interfaces. Farmers with limited literacy can now ask questions in regional dialects and receive AI-curated guidance on disease management or market pricing. In sub-Saharan Africa, mobile-based NLP platforms are delivering customized weather updates and planting tips to over a million users. These systems integrate with national databases to deliver hyper-local recommendations based on soil profiles and crop history. NLP also enables two-way communication, allowing extension workers to gather field insights at scale. This democratized information flow is narrowing the knowledge gap in global agriculture.

• Integration with Blockchain for Supply Chain Transparency

Blockchain integration is creating tamper-proof, real-time records of every stage in the agricultural value chain. When combined with AI, these systems offer predictive analytics on spoilage, fraud detection, and optimal logistics routing. For example, an AI-blockchain hybrid used in Southeast Asia tracks shrimp from pond to plate, ensuring transparency and regulatory compliance. AI algorithms flag anomalies such as temperature breaches in cold chains or mismatched batch records. This fosters accountability across producers, distributors, and retailers. As food authenticity becomes a consumer priority, such systems are boosting trust and unlocking premium pricing opportunities for certified, traceable products.

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Leading Companies Operating in the Global AI in Agriculture Industry:

• A.A.A Taranis Visual Ltd.
• Ag Leader Technology
• AgEagle Aerial Systems Inc.
• Bayer AG
• Deere & Company
• Gamaya
• Granular Inc. (DuPont de Nemours, Inc.)
• International Business Machines Corporation
• Raven Industries Inc.
• Trimble Inc.
• Oracle Corporation
• Wipro Limited

AI in Agriculture Market Report Segmentation:

Analysis By Offering:

• Software
• Hardware
• AI-as-a-Service
• Services

Software represents the largest segment due to the increasing adoption of AI-powered software solutions for crop management and yield optimization.

Analysis By Technology:

• Machine Learning
• Computer Vision
• Predictive Analytics

Machine learning accounts for the biggest segment as it enables advanced data analysis and predictive modeling for precision agriculture.

Analysis By Application:

• Precision Farming
• Agriculture Robots
• Livestock Monitoring
• Drone Analytics
• Labor Management
• Others

Precision Farming exhibits clear dominance as it offers farmers enhanced control over crop production and resource utilization.

Regional Insights:

• North America (United States, Canada)
• Asia Pacific (China, Japan, India, South Korea, Australia, Indonesia, Others)
• Europe (Germany, France, United Kingdom, Italy, Spain, Russia, Others)
• Latin America (Brazil, Mexico, Others)
• Middle East and Africa

Research Methodology:

The report employs a comprehensive research methodology, combining primary and secondary data sources to validate findings. It includes market assessments, surveys, expert opinions, and data triangulation techniques to ensure accuracy and reliability.

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IMARC Group is a global management consulting firm that helps the world’s most ambitious changemakers to create a lasting impact. The company provide a comprehensive suite of market entry and expansion services. IMARC offerings include thorough market assessment, feasibility studies, company incorporation assistance, factory setup support, regulatory approvals and licensing navigation, branding, marketing and sales strategies, competitive landscape and benchmarking analyses, pricing and cost research, and procurement research.

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