Artificial Intelligence in Agriculture Market Emerging Trends & Opportunities and It is Segmented by Application (weather Tracking, Precision Farming, Drone Analytics), Deployment (cloud, On-Premises, Hybrid), and Geography (North America, Europe, Asia-Pacific, and the Rest of the World). The Market Size and Forecasts are Provided in Terms of Value in USD for all the Above Segments.

About the Dataset

AI-Driven Agricultural Optimization: Sustainable Farming Insights

This dataset is designed to support the development of a multi-agent AI system aimed at optimizing farming practices while promoting sustainability. It integrates data from farmers, weather stations, and market trends to enable AI-driven decision-making for resource-efficient and profitable agriculture.

Dataset Composition

• Farmer Data: Land characteristics, crop preferences, financial constraints, and past yield records.
• Weather & Soil Data: Rainfall, temperature, humidity, soil moisture, and other climate-related variables affecting crop growth.
• Market Trends: Regional crop pricing, demand forecasts, and trade patterns to help farmers maximize profits.
• Sustainability Metrics: Water usage, pesticide application, carbon footprint, and soil health indicators for eco-friendly farming recommendations.

This dataset serves as a foundation for building intelligent AI solutions that help reduce environmental impact, optimize agricultural resources, and enhance farmers' decision-making.

Artificial intelligence is deployed in agriculture mainly in field, livestock, and indoor farming in 2019. Field farming is the main farming type where AI is used in agriculture, with a market share of more than ***. The overall AI in agriculture market had a size of almost *** billion U.S. dollars in 2019 and is forecast to grow to more than *** billion U.S. dollars by 2024.

The AI in agriculture market size is projected to grow from USD 2.14 billion in 2024 to USD 20.96 billion by 2035, representing a CAGR of 23.06%, during the forecast period till 2035

Netherlands AI in Agriculture Market was valued at USD 101.27 Million in 2023 and is anticipated to reach USD 155.09 Million with a CAGR of 7.44% through the forecast period.

According to Cognitive Market Research, the global Artificial Intelligence in Agriculture market size is USD 1.9 billion in 2024 and will expand at a compound annual growth rate (CAGR) of 20.56% from 2024 to 2031.

Market Dynamics of Artificial Intelligence in Agriculture Market

Key Drivers for Artificial Intelligence in the Agriculture Market



  Increasing Population and Demand for Food to Increase the Demand Globally - One key driver in the Artificial Intelligence in Agriculture market is the rising demand for food growing population. As the global population continues to surge, there is an surging demand for food production to meet the needs of a larger populace. This growing demand poses significant challenges to traditional agricultural practices in terms of efficiency, productivity, and sustainability. Artificial Intelligence (AI) offers innovative solutions by optimizing various aspects of farming, such as crop monitoring, yield prediction, and resource management. By harnessing AI technologies, farmers can enhance their productivity and maximize yields while minimizing resource wastage.


  Supportive Government Policies and the Initiatives to Promote Modern Agricultural Tools and Techniques Drive the Market by Fostering Technological Adoption, Incentivizing Innovation, and Facilitating the Integration of AI Solutions into Farming Practices.




Key Restraints for Artificial Intelligence in the Agriculture Market



  High-Cost and Unskilled Labor- The high initial cost of installation and unskilled labor is a significant barrier to market growth.


  Large-Scale Technological Limitations in Underdevelopment Economies- Large-scale technological limitations in underdeveloped economies hinder the widespread adoption and growth of Artificial Intelligence in the Agriculture market by impeding access to necessary infrastructure and resources for deploying AI-powered solutions effectively.

Introduction of the Artificial Intelligence in Agriculture Market

Integration of the Artificial Intelligence (AI) in agriculture has revolutionized the industry by enhancing efficiency, productivity, and sustainability. AI technologies like computer vision, ML, and predictive analytics are being deployed to optimize various agricultural processes. These include crop monitoring, yield prediction, disease detection, precision farming, and resource management. AI-powered systems analyze vast amounts of data collected from drones, sensors, and satellite imagery to provide actionable insights for farmers, enabling them to make informed decisions and maximize yields while minimizing resource wastage. Additionally, AI solutions contribute to mitigating environmental impact by reducing chemical usage and optimizing water usage. The global AI in agriculture market is experiencing fast growth, driven by the surging adoption of smart farming practices, government initiatives promoting digitalization in agriculture, and growing demand for food security amidst population growth and climate change challenges.

Artificial Intelligence in Agriculture Market Outlook

According to our latest research, the global Artificial Intelligence (AI) in Agriculture market size reached USD 2.2 billion in 2024. The market is experiencing robust growth, driven by the increasing adoption of advanced technologies in the agricultural sector, with a compound annual growth rate (CAGR) of 23.6% projected from 2025 to 2033. By the end of 2033, the market is forecasted to reach an impressive USD 17.3 billion. This remarkable expansion is primarily attributed to the growing demand for precision farming, increased investments in agri-tech startups, and the pressing need to enhance crop yields and farm productivity globally.

One of the most significant growth factors for the AI in agriculture market is the urgent need to optimize resource utilization and increase efficiency in food production. As the global population continues to rise, food demand is outpacing traditional agricultural methods. AI-driven solutions such as predictive analytics, machine learning, and computer vision are enabling farmers to make data-driven decisions, minimize waste, and maximize output. These technologies help in early detection of crop diseases, real-time monitoring of soil health, and precise application of fertilizers and pesticides. The integration of AI-powered sensors and IoT devices is transforming conventional farming into smart agriculture, offering actionable insights that enable farmers to address challenges proactively and sustainably.

Another key driver fueling the growth of the AI in agriculture market is the rapid advancement in agricultural robotics and drone analytics. The deployment of AI-enabled drones for aerial surveillance and crop monitoring has revolutionized field management, making it possible to cover large areas in a fraction of the time compared to manual methods. Agricultural robots are increasingly being used for tasks such as planting, harvesting, and weed control, reducing labor costs and improving operational efficiency. These innovations are particularly beneficial in regions facing labor shortages and rising wage pressures. Furthermore, the integration of robotics with AI technologies enhances the precision and effectiveness of farm operations, leading to higher yields and better quality produce.

Government initiatives and supportive policies are also playing a vital role in propelling the AI in agriculture market. Several countries are investing heavily in digital infrastructure and offering subsidies or incentives for the adoption of smart farming technologies. Public-private partnerships and collaborations between research institutes, technology providers, and agricultural cooperatives are accelerating the commercialization of AI solutions. Additionally, the emergence of agri-tech startups and increased venture capital funding are fostering innovation and driving competition in the market. These factors collectively contribute to the rapid uptake of AI technologies across diverse agricultural landscapes, from smallholder farms to large commercial enterprises.

Regionally, North America dominates the AI in agriculture market, owing to its advanced technological ecosystem, high level of digital literacy among farmers, and strong government support for innovation. However, Asia Pacific is emerging as the fastest-growing region, with countries like China and India investing significantly in AI-driven agricultural solutions to address food security challenges and improve farm productivity. Europe is also witnessing substantial growth, driven by stringent environmental regulations and the adoption of precision farming practices. Latin America and the Middle East & Africa are gradually catching up, with increasing awareness about the benefits of AI in agriculture and rising investments in smart farming infrastructure.

Offering Analysis

The offering segment of the AI in agriculture market is br

According to Cognitive Market Research, the Global AI in Agriculture market size will be USD 2142.20 million in 2024. It will expand at a compound annual growth rate (CAGR) of 23.50% from 2024 to 2031.

North America held the major market share for more than 40% of the global revenue with a market size of USD 856.88 million in 2024 and will grow at a compound annual growth rate (CAGR) of 21.7% from 2024 to 2031.
Europe accounted for a market share of over 30% of the global revenue with a market size of USD 642.66 million.
Asia Pacific held a market share of around 23% of the global revenue with a market size of USD 492.71 million in 2024 and will grow at a compound annual growth rate (CAGR) of 25.5% from 2024 to 2031.
Latin America had a market share of more than 5% of the global revenue with a market size of USD 107.11 million in 2024 and will grow at a compound annual growth rate (CAGR) of 22.9% from 2024 to 2031.
Middle East and Africa had a market share of around 2% of the global revenue and was estimated at a market size of USD 42.54 million in 2024 and will grow at a compound annual growth rate (CAGR) of 23.2% from 2024 to 2031.
The Machine Learning category is the fastest growing segment of the AI in Agriculture industry

Market Dynamics of AI in Agriculture Market

Key Drivers for AI in Agriculture Market

Increasing Demand for Food Production to Boost Market Growth

The increasing demand for food production is a key driver of AI in the agriculture market due to the rising global population, which is expected to reach nearly 10 billion by 2050. Farmers need to produce more food while facing challenges like limited arable land, water scarcity, and climate change. AI helps address these issues by optimizing resource use, improving crop yields, and enabling precision farming techniques that minimize waste. Technologies like AI-powered drones, sensors, and predictive analytics allow farmers to monitor crop health, predict weather patterns, and make data-driven decisions, resulting in more efficient and sustainable farming practices. This growing need for higher productivity is pushing the adoption of AI solutions in agriculture.

For instance, in April 2024, John Deere unveiled autonomous tractors and trucks at CES, aiming to address labor shortages and increase productivity in agriculture. (Source: https://www.theverge.com/2025/1/6/24334357/john-deere-autonomous-tractor-truck-orchard-mow-ces?)

Rising Adoption of Precision Farming to Drive Market Growth

The rising adoption of precision farming is driving the AI in agriculture market as farmers increasingly seek data-driven solutions to improve efficiency, reduce costs, and maximize crop yields. Precision farming leverages AI technologies like machine learning, GPS-guided equipment, and sensors to analyze vast amounts of data related to soil conditions, weather, and crop health. AI enables real-time monitoring and predictive insights, allowing farmers to make informed decisions about planting, fertilizing, and irrigation with pinpoint accuracy. This targeted approach minimizes resource waste, such as water and fertilizers, while optimizing output. As environmental sustainability and profitability become more critical, the growing demand for precision farming is accelerating the integration of AI technologies in agricultural practices worldwide.

Key Restraint for the AI in Agriculture Market

Limited Digital Infrastructure in Rural Areas

Limited digital infrastructure in rural areas is a significant restraint on the AI in agriculture market because many AI-driven technologies depend on robust internet connectivity, cloud computing, and data transfer capabilities. Rural regions, where most agricultural activities occur, often lack access to reliable, high-speed internet and advanced communication networks. This hampers the deployment of AI tools such as remote sensors, drones, and real-time data analytics, which require continuous connectivity for effective operation. Without the necessary infrastructure, farmers in these areas are unable to fully utilize AI technologies, limiting the scalability and adoption of precision farming solutions. As a result, the digital divide in rural regions poses a challenge to widespread AI adoption in agriculture, slowing the market’s growth.

For instance, in January 2025, a report highlighted that AI agritech startup...

Global artificial intelligence in agriculture market, valued at $1,820.2 million in 2023, will reach $12,478.6 million by 2034, growing at a CAGR of 18.95% from 2024 to 2034.

The value of artificial intelligence in the global agriculture market was estimated to be around *** billion U.S. dollars in 2023 and is forecast to grow to about *** billion U.S. dollars by 2028.

Germany AI in Agriculture Market was valued at USD 350.77 Million in 2023 and is anticipated to project impressive growth in the forecast period with a CAGR of 8.14% through 2029.

AI in Agriculture Market Outlook

The global AI in agriculture market size is projected to grow from USD 1.2 billion in 2023 to USD 4.3 billion by 2032, exhibiting a CAGR of 15.5% during the forecast period. This impressive growth is driven by the increasing need for efficient and sustainable farming practices to meet the rising global food demand. Factors such as advancements in AI technologies, the adoption of smart farming techniques, and supportive government initiatives are major contributors to this growth.

One of the significant growth factors in the AI in agriculture market is the escalating global population, which necessitates increased food production. Traditional farming methods are insufficient to meet this demand, leading to the adoption of AI-driven solutions that enhance productivity and efficiency. AI technologies, such as predictive analytics, help farmers make informed decisions about crop management, pest control, and irrigation, ultimately improving yields and reducing waste. This shift towards precision agriculture is a vital driver of market growth.

Another crucial growth factor is the rising trend of digital transformation in agriculture. With the advent of the Internet of Things (IoT), farmers can now monitor field conditions in real-time using sensors and drones. These devices collect vast amounts of data, which AI algorithms can analyze to provide actionable insights. This integration of AI and IoT in agriculture not only optimizes resource utilization but also mitigates the risks associated with unpredictable weather patterns and pests, thereby enhancing overall farm productivity.

Furthermore, government initiatives and policies supporting the adoption of AI in agriculture are fueling market growth. Many governments around the world are investing in agricultural research and development to promote sustainable farming practices. Subsidies and grants for adopting AI technologies are encouraging farmers to embrace these innovations. Additionally, collaborations between public and private sectors are accelerating the deployment of AI solutions, making advanced farming techniques accessible to a broader range of farmers, including those in developing regions.

Regionally, North America is expected to hold the largest market share due to the early adoption of advanced technologies and the presence of major AI solution providers. Europe is also anticipated to experience significant growth, driven by the increasing focus on sustainable farming practices and stringent environmental regulations. The Asia Pacific region is projected to witness the highest growth rate owing to the large agricultural sector and the growing awareness of AI benefits among farmers. Latin America and the Middle East & Africa are also expected to show steady growth, supported by government initiatives and investments in agricultural innovation.

Component Analysis

The AI in agriculture market is segmented by components into hardware, software, and services. The hardware segment includes devices such as sensors, drones, and automated machines, which are essential for data collection and real-time monitoring. The rapid advancement in sensor technology has made it possible to gather precise data on various farming parameters, such as soil moisture, temperature, and crop health. These sensors, when integrated with AI algorithms, provide valuable insights that help farmers make informed decisions, improving crop yields and resource management. The hardware segment is expected to witness substantial growth as more farmers adopt these technologies to enhance their farming practices.

The software segment encompasses various AI applications and platforms designed to analyze data and provide actionable insights. This includes predictive analytics software, farm management systems, and AI-driven decision support tools. These software solutions enable farmers to optimize their operations by predicting weather conditions, pest infestations, and crop diseases. The increasing demand for data-driven decision-making in agriculture is propelling the growth of the software segment. Additionally, advancements in cloud computing and machine learning algorithms are further enhancing the capabilities of agricultural software, making it an indispensable tool for modern farming.

The services segment includes consulting, implementation, and maintenance services provided by AI solution providers. These services are crucial for the successful deployment and operation of AI technologies in agriculture. Consulting services help farmers understand the potenti

China AI in Agriculture Market was valued at USD 148.24 Million in 2023 and is anticipated to reach USD 232.15 Million with a CAGR of 7.84% through 2029.

The global market for Artificial Intelligence (AI) in Precision Farming is experiencing robust growth, projected to reach $577.2 million in 2025 and exhibiting a Compound Annual Growth Rate (CAGR) of 18.1% from 2025 to 2033. This expansion is driven by several factors. Firstly, the increasing need for enhanced crop yields and efficient resource management in agriculture is fueling the adoption of AI-powered solutions. Precision farming techniques, enabled by AI, optimize irrigation, fertilization, and pest control, leading to significant cost savings and improved profitability for farmers. Secondly, advancements in machine learning, computer vision, and sensor technologies are providing more sophisticated and accurate data analysis, enabling predictive modelling for crop health, weather patterns, and yield estimation. The integration of AI with various farm equipment, such as drones and tractors, further streamlines operations and improves efficiency. Finally, growing government support and initiatives focused on promoting technological advancements in agriculture are fostering innovation and market expansion. Key segments driving growth include machine learning algorithms for data analysis and computer vision for image-based crop monitoring, particularly within the farm management and private planting applications. Major players like Microsoft, IBM, John Deere, and numerous agricultural technology startups are actively contributing to this dynamic market landscape, developing and deploying cutting-edge AI solutions for farmers worldwide. The regional distribution of the market is expected to reflect global agricultural trends, with North America and Europe likely to hold substantial market shares due to advanced technological infrastructure and high adoption rates. However, the Asia-Pacific region, particularly India and China, is predicted to experience significant growth in the coming years owing to the large agricultural sector and increasing investments in agricultural technology. The "Others" segments in both type and application will likely experience substantial growth as AI technology matures and finds new applications in addressing specific agricultural challenges and niche markets. Further market penetration will depend on factors such as the affordability and accessibility of AI-powered tools, along with farmer training and digital literacy initiatives. While some restraints remain, such as the high initial investment costs and data security concerns, the long-term potential for AI in precision farming remains substantial.

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. North America currently dominates the market, holding a significant market share of over 36.8% in 2024, driven by the increasing need for precision agriculture techniques to enhance crop yield, and the growing adoption of IoT devices and sensors for data-driven farming practices.

IMARC Group provides an analysis of the key trends in each segment of the global AI in agriculture market, along with forecast at the global, regional, and country levels from 2025-2033. The market has been categorized based on offering, technology, and application.

The global Artificial Intelligence (AI) in Agriculture market, valued at $740.2 million in 2025, is poised for significant growth. Driven by the increasing need for precision farming techniques, rising adoption of automation in agricultural processes, and the growing awareness of sustainable agriculture practices, this sector is experiencing a rapid expansion. Key applications like precision farming, drone analytics, and agricultural robotics are witnessing substantial adoption. Machine learning and computer vision technologies are the primary drivers, enabling real-time data analysis, improved crop yield predictions, and optimized resource management. The market is fragmented, with a mix of established players like IBM, John Deere, and Microsoft, alongside several innovative startups such as Agribotix, Prospera, and FarmBot focusing on specialized solutions. North America currently holds a dominant market share, fueled by early adoption and robust technological advancements. However, regions like Asia-Pacific are exhibiting rapid growth potential, driven by increasing investment in agricultural technologies and a rising demand for food security. Challenges remain, including high initial investment costs, data security concerns, and the need for robust infrastructure to support AI-driven agricultural practices. Despite these challenges, the long-term outlook for AI in agriculture remains extremely positive, indicating considerable growth opportunities for businesses across the value chain. The market is expected to experience substantial growth throughout the forecast period (2025-2033). While a specific CAGR wasn't provided, a conservative estimate, considering the technological advancements and market trends, would place the annual growth rate between 15% and 20%. This suggests a substantial market expansion, exceeding $2 billion by 2033. The continued development of more affordable and user-friendly AI-powered agricultural tools will be key to unlocking further growth, particularly in developing economies. Furthermore, government initiatives promoting technological adoption in agriculture are likely to further accelerate market expansion. The integration of AI with other technologies, such as IoT and blockchain, will present even more opportunities for innovation and efficiency improvements in the agricultural sector.

The market size for AI in agriculture is projected to be $2,252 million in 2025, exhibiting a CAGR of 16.0% from 2019 to 2033. Key drivers include increasing demand for food production, labor shortages, and government initiatives promoting precision agriculture. AI technologies such as machine learning, computer vision, and predictive analytics optimize crop yields, improve livestock management, and enhance efficiency in various farming operations. Leading companies like IBM, Microsoft, and John Deere are investing heavily in AI solutions, while start-ups like Agribotix and Spensa Technologies are emerging as key players. Regionally, North America is expected to hold a significant market share due to early adoption of AI and advanced agriculture practices. Asia Pacific is anticipated to witness substantial growth, driven by increasing investment in agriculture and government support for digital farming. Europe is projected to remain a significant market, with countries like Germany, France, and Spain implementing AI technologies to improve agricultural productivity. The Middle East & Africa and South America are emerging markets with potential for growth as adoption of AI in agriculture gains traction. Artificial Intelligence (AI) has the potential to revolutionize the agricultural industry by providing farmers with the tools they need to increase productivity, reduce costs, and improve sustainability. The global AI in agriculture market is expected to grow from USD 1.2 billion in 2019 to USD 8.1 billion by 2026, at a CAGR of 25.5%.

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The artificial intelligence (AI) market in agriculture market share is expected to increase by USD 458.68 million from 2020 to 2025, and the market’s growth momentum will accelerate at a CAGR of 23.34%.

This artificial intelligence (AI) market in agriculture market research report provides valuable insights on the post COVID-19 impact on the market, which will help companies evaluate their business approaches. Furthermore, this report extensively covers artificial intelligence (AI) market in agriculture market segmentations by application (robotics, crop and soil management, and animal husbandry) and geography (North America, Europe, APAC, South America, and MEA). The artificial intelligence (AI) market in agriculture market report also offers information on several market vendors, including Ag Leader Technology, aWhere Inc., Corteva Inc., Deere & Co., DTN LLC, GAMAYA, International Business Machines Corp., Microsoft Corp., Raven Industries Inc., and Trimble Inc. among others.

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Artificial Intelligence (AI) Market In Agriculture Market: Key Drivers, Trends, and Challenges

Maximizing profits in farm operations is notably driving the artificial intelligence (AI) market in agriculture market growth, although factors such as technical difficulties in developing AI technologies may impede the market growth. Our research analysts have studied the historical data and deduced the key market drivers and the COVID-19 pandemic impact on the artificial intelligence (AI) market in the agriculture market industry. The holistic analysis of the drivers will help in deducing end goals and refining marketing strategies to gain a competitive edge.

Key Artificial Intelligence (AI) Market In Agriculture Market Driver

Maximizing profits in farm operations is a major driver fueling the artificial intelligence market in agriculture market growth. To increase profits in farm operations, the yield and output of crops and animals must be maximized, respectively. AI technology incorporated in the form of robots, drones, crop management systems, and herd management tools enables farms to monitor and regulate remote operations and provide logical data to analyze several aspects of an agriculture farm. Smart or precision agriculture is rapidly emerging as a technology that will help farmers to enhance the deliverables in agriculture. With AI technologies on the rise, farmers can control and monitor the equipment, crop, and livestock through their smartphones and also receive statistical predictions for crops and livestock. Smart sensors, satellite imagery, and other cloud-based technologies are highly beneficial to observe and record data during crop planting and harvesting, thereby maximizing production output and minimizing the cost of resources wasted. In animal husbandry, advanced AI technologies, through sensors and visual imaging, can quickly analyze the health and physical well-being of a particular animal and flag deviations in case of any disease or ailment. In this way, the animal can be treated in due course of time without spreading the infection to other animals. Such timely monitoring also saves money, as the farmers need not wait for any symptom to arise in detecting abnormal animal health and take minor precautionary steps to induce recovery in the affected animal.

Key Artificial Intelligence (AI) Market In Agriculture Market Trend

Maximizing profits in farm operations is a major trend influencing the artificial intelligence market in agriculture market growth. To increase profits in farm operations, the yield and output of crops and animals must be maximized, respectively. AI technology incorporated in the form of robots, drones, crop management systems, and herd management tools enable farms to monitor and regulate remote operations and provide logical data to analyze several aspects of an agriculture farm. Smart or precision agriculture is rapidly emerging as a technology that will help farmers to enhance the deliverables in agriculture. With AI technologies on the rise, farmers can control and monitor the equipment, crop, and livestock through their smartphones and also receive statistical predictions for crops and livestock. Smart sensors, satellite imagery, and other cloud-based technologies are highly beneficial to observe and record data during crop planting and harvesting, thereby maximizing production output and minimizing the cost of resources wasted. In animal husbandry, advanced AI technologies, through sensors and visual imaging, can quickly analyze the health and physical well-being of a particular animal and flag deviations in case of any disease or ailment. In th

The AI in Agriculture market is experiencing robust growth, projected to reach $2.08 billion in 2025 and expand significantly over the forecast period (2025-2033). A compound annual growth rate (CAGR) of 22.55% indicates a rapidly evolving landscape driven by several key factors. Increased demand for precision farming techniques, enabling optimized resource allocation and enhanced crop yields, is a major driver. The ability of AI to analyze large datasets from various sources, including weather patterns, soil conditions, and drone imagery, provides actionable insights leading to improved decision-making for farmers. Furthermore, advancements in machine learning and computer vision are fueling the development of sophisticated AI-powered tools for tasks such as automated weed detection, disease prediction, and yield forecasting. The market is segmented by application (weather tracking, precision farming, drone analytics) and deployment (cloud, on-premise, hybrid), reflecting diverse technological implementations and user needs. Leading companies like Microsoft, IBM, and several specialized agricultural AI firms are actively shaping this market with innovative solutions. The continued adoption of AI across various agricultural practices is expected to propel market expansion. The cloud-based deployment model is likely to dominate due to its scalability and accessibility. While challenges remain, such as data security concerns and the need for robust infrastructure, the overall market trajectory suggests considerable potential. The integration of AI into existing agricultural workflows will continue to be crucial, necessitating collaborative efforts between technology providers and agricultural stakeholders. Regional variations in technology adoption rates are anticipated, with North America and Europe likely leading the market initially, followed by a gradual increase in adoption across Asia and other regions as awareness and technological infrastructure improve. The long-term forecast indicates strong potential for growth as AI becomes more integrated and accessible to a wider range of farmers globally. Recent developments include: August 2024: The Union Government unveiled the AI-driven National Pest Surveillance System (NPSS), enabling farmers to consult agricultural scientists and pest control experts directly via their phones. Leveraging AI tools, NPSS will scrutinize up-to-date pest data, assisting both farmers and experts in effective pest management. According to the Ministry, NPSS aims to benefit approximately 140 million farmers nationwide. The Centre envisions this platform as a bridge, linking scientists directly to the agricultural fields., July 2024: Google launched its Agricultural Landscape Understanding (ALU) tool, designed to equip farmers with vital agricultural insights and enhance crop yields. This tool, available in limited capacity, seeks to transform agricultural practices into data-driven endeavors. Leveraging high-resolution satellite imagery and machine learning, the ALU will delineate field boundaries and provide insights on drought preparedness, irrigation, and market access, among other features.. Key drivers for this market are: Maximize Crop Yield Using Machine Learning technique, Increase in the Adoption of Cattle Face Recognition Technology; Increase Use of Unmanned Aerial Vehicles (UAVs) Across Agricultural Farms. Potential restraints include: Maximize Crop Yield Using Machine Learning technique, Increase in the Adoption of Cattle Face Recognition Technology; Increase Use of Unmanned Aerial Vehicles (UAVs) Across Agricultural Farms. Notable trends are: Drone Analytics Application Segment is Expected to Hold Significant Market Share.

The global Artificial Intelligence (AI) in Agriculture market size reached USD 1.70 Billion in 2021 and is expected to reach USD 13.89 Billion in 2030 registering a CAGR of 27.0%. AI in Agriculture industry report classifies global market by share, trend, growth and based on component, technology, a...