Home Technology AI in Agriculture Market Size, Share Analysis, Growth and Forecast to 2031

AI in Agriculture Market

AI in Agriculture Market Size, Share & Trends Analysis Report By Offering (Hardware, Software, AI-as-a-Service, Service), By Technology (Machine Learning, Computer Vision, Predictive Analytics, Natural Language Processing), By Applications (Precision Farming, Livestock Monitoring, Drone Analytics, Agriculture Robots, Labor Management, Crop Management, Irrigation Management, Others), By End User (Farmers/Growers, Agriculture Cooperatives, Food Processing Companies, Others) and By Region(North America, Europe, APAC, Middle East and Africa, LATAM) Forecasts, 2023-2031

Report Code: SRTE65DR
Study Period 2019-2031 CAGR 25%
Historical Period 2019-2021 Forecast Period 2023-2031
Base Year 2022 Base Year Market Size USD 1 Billion
Forecast Year 2031 Forecast Year Market Size USD 5.96 Billion
Largest Market North America Fastest Growing Market Asia-Pacific

Market Overview

The global AI in agriculture market size was valued at USD 1 billion in 2022. It is projected to reach USD 5.96 billion by 2031, growing at a CAGR of 25% during the forecast period (2023–2031). Artificial intelligence (AI) in agriculture uses cognitive technology to improve farming's capacity for learning, reasoning, understanding, and interaction. 

Artificial intelligence (AI) is now commonly used in the agricultural sector to increase crop yields without sacrificing quality. Farmers' attention has shifted from conventional farming techniques to refining the product through enhanced farming methods like drones, automated systems, and robots due to the increased research and development of sophisticated robotics technology in the agriculture industry. As a result, farmers now employ more advanced techniques. Due to rising demand, farmers are investing in more efficient farming methods, which necessitate implementing automated farming systems.

Market Dynamics

Global AI in Agriculture Market Drivers

Rising Need for Real-Time Livestock Monitoring

One of the most crucial trends in artificial intelligence in agriculture is the growing requirement for livestock monitoring. Dairy farms may now individually monitor all behavioral characteristics of a herd using advanced AI technologies such as facial recognition for animals and picture classification along with body condition score and feeding patterns. It has the potential to cause a revolutionary shift in how farmers view farmlands, both in terms of time and effort. Moreover, farmers are increasingly employing machine vision to distinguish hide patterns and facial features, monitor water and food consumption, record body temperature, and track behavior to keep tabs on the health of their cattle.

Global AI in Agriculture Market Restraint

Lack of Experience with Emerging Technologies

It's essential to recognize the differences between the agricultural sectors of developed countries and emerging ones. Artificial intelligence agriculture could be helpful in some places, but it could be challenging to sell in areas where that kind of thing is still uncommon. Most farmers will require assistance in implementing it. Farmers frequently regard AI as being limited to the digital realm. They may not appreciate how this technology can improve their ability to cultivate the land. It's not because they're old-fashioned or scared of change. Their opposition stems from a lack of knowledge of the practical application of AI tools. However, there is much work to be done by technology vendors to assist farmers in properly implementing AI.

Global AI in Agriculture Market Opportunities

Agricultural Labor Force is Steadily Decreasing

A shortage of qualified workers, aging farmers, and younger generations who find farming unappealing all contribute to the downturn, driving trends toward automated farming operations. As the number of people working in agriculture continues to drop, public and commercial institutions are increasingly investing in artificial intelligence (AI)-based automation solutions to alleviate labor shortages. The developed world is not immune to this downward trend. The agricultural sector in Asia and the Pacific is experiencing a severe labor shortage due to an aging population. Due to the causes mentioned above, the market for artificial intelligence in agriculture is projected to flourish in the following years.

Regional Analysis

The global AI in agriculture market is bifurcated into four regions, namely North America, Europe, Asia-Pacific, and LAMEA.

North America Dominates the Global Market

North America is the most significant shareholder in the global AI in the agriculture market and is expected to grow during the forecast period. Increases in disposable income, ongoing funding for automation, big bets on the Internet of Things, and a growing emphasis from governments on homegrown AI equipment development are all hallmarks of the North American economy. The market also benefits from various agricultural technology vendors researching artificial intelligence solutions. Artificial intelligence (AI) is projected to usher in a technological revolution in the future of farming techniques in the region, with drones, robots, and intelligent monitoring systems being deployed in research and field experiments. Additionally, the regional market is anticipated to be driven by the increasing use of AI-powered technologies in the agricultural sector. In addition, the growing popularity of Internet of Things (IoT) devices in agriculture are anticipated to boost the worldwide AI in the agriculture market in the area.

Asia-Pacific is expected to grow during the forecast period. Rapid expansion is attributed to the expanding use of AI tools in farming. India and China, two of the world's fastest-growing economies, are using artificial intelligence (AI) technologies like remote monitoring and predictive analysis in the food business. Furthermore, the growing demand in these economies for smart cities is prompting agribusiness enterprises to implement AI-powered solutions and services. China is seeing a significant increase in the adoption of AI solutions in agriculture in the region, mainly to Alibaba Group's entry into the agricultural solution market with its AI technology to aid small farmers in the country.

Al is used for row crop cultivation. The robot is so effective at weeding rows of crops that only a twentieth as much herbicide is needed. The European Soil Data Centre is Europe's thematic focus for soil-related data. Its purpose is to act as a central repository for all relevant soil data and information on a European scale. The increasing popularity of Al in agriculture can be attributed to the widespread adoption of AI and computer vision-based monitoring and reporting technologies for indoor and outdoor fields. With over a thousand operating indoor farms in Germany and expansion into other European countries, the demand for Al in agriculture is increasing.

Due to the increasing popularity of AI-powered systems that employ deep learning methods, LAMEA is predicted to have moderate expansion. The global AI in the agriculture market is expected to expand at a staggering rate due to the increasing prevalence of applications that combine IoT and AI, such as predictive analysis, machine learning, and others. Despite the progress made over the previous two decades in agricultural innovation initiatives, there is still a pressing need to fortify agricultural research, technology, and innovation infrastructure to meet these problems.

Report Scope

Report Metric Details
By Offering
  1. Hardware
  2. Software
  3. AI-as-a-Service
  4. Service
By Technology
  1. Machine Learning
  2. Computer Vision
  3. Predictive Analytics
  4. Natural Language Processing
By Applications
  1. Precision Farming
  2. Livestock Monitoring
  3. Drone Analytics
  4. Agriculture Robots
  5. Labor Management
  6. Crop Management
  7. Irrigation Management
  8. Others
By End User
  1. Farmers/Growers
  2. Agriculture Cooperatives
  3. Food Processing Companies
  4. Others
Company Profiles IBM John Deere Trimble AGCO Corporation GAMAYA PrecisionHawk VineView Vision Robotics Corporation INC. Farmers Edge Corteva Agriscience Microsoft Corporation Trace Genomics INC. Connecterra Harvest Croo. DeLaval Taranis
Geographies Covered
North America U.S. Canada
Europe U.K. Germany France Spain Italy Russia Nordic Benelux Rest of Europe
APAC China Korea Japan India Australia Taiwan South East Asia Rest of Asia-Pacific
Middle East and Africa UAE Turkey Saudi Arabia South Africa Egypt Nigeria Rest of MEA
LATAM Brazil Mexico Argentina Chile Colombia Rest of LATAM
Report Coverage Revenue Forecast, Competitive Landscape, Growth Factors, Environment & Regulatory Landscape and Trends
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Segmental Analysis

The global AI in agriculture market is segmented by component, technology, and application.

Based on components, the global AI in agriculture market is bifurcated into solutions and services.

The solution segment is the highest contributor to the market and is expected to grow during the forecast period. IBM, Microsoft, and Deere & Company are just a few well-known firms offering Al-based software solutions tailored to the agricultural industry. Al-based software boosts crop productivity and yield through the use of analytics based on future predictions and computer vision. Increased adoption of predictive analytics software has also contributed to the expansion of this market sub-segment. Examples of popular software that uses predictive analytics include IBM's Watson Decision Platform and Microsoft's Al Sowing App. These AI tools help farmers calculate the ideal times to plant seeds, find signs of plant diseases, keep tabs on harvest success, and figure out how much space, water, fertilizer, and pesticides their crops need.

Based on technology, the global AI in agriculture market is bifurcated into machine learning, computer vision, and predictive analytics.

The machine learning segment is the highest contributor to the market and is expected to grow during the forecast period. It is due to farmers' increased embrace of advanced revolutionary technology in the agriculture industry. Additionally, the use of machine learning technology by farmers worldwide is anticipated to drive market expansion in this area. Machine learning aids farmers and agricultural enterprises in making more informed decisions by analyzing real-time data on weather, temperature, crop status, and other variables. Machine learning's capabilities in these areas will drive the expansion of the artificial intelligence (AI) business into the agricultural sector. The rapid growth is also because farm managers and producers utilize IoT devices' capabilities for mapping fields and controlling irrigation systems.

Based on application, the global AI in agriculture market is bifurcated into precision farming, livestock monitoring, drone analytics, agriculture robots, and others.

The precision farming segment is the highest contributor to the market and is expected to grow during the forecast period. Precision farming is one of the most rapidly increasing AI-enabled agricultural applications. It helps farmers to cut expenses and make the most of available resources. Automated intelligence is used to collect, interpret, and analyze digital data for precision farming. Due to the rising population and the need for better food quality, precision farming applications center on improving farm output. With the help of precision farming, farmers can abandon time-honored practices in favor of cutting-edge ways that streamline and simplify farming. With the help of research and projections, farmers can adjust the amount of fertilizer or pesticide they use.

Market Size By Offering

Recent Developments

  • April 2023- IBM and Texas A&M AgriLife collaborated to provide farmers with water consumption insights, which can boost agricultural productivity while lowering economic and environmental expenses. Texas A&M AgriLife and IBM will deploy and grow Liquid Prep, a technology solution that helps farmers decide "when to water" in dry parts of the United States.
  • May 2022- AGRA and Microsoft expanded their collaboration to help with the digital agricultural transformation. AGRA and Microsoft signed an MoU in Davos for future collaboration through its Africa Transformation Office. The organizations will leverage their success from a previous partnership started in 2019, which led to the development of the AgriBot.
  • October 2022- Thermo Fisher Scientific Inc., the world's largest provider of scientific instruments and services, has announced a definitive deal to purchase The Binding Site Consortium, a market leader in specialty diagnostics, from an investor group led by Nordic Capital.
  • September 2022- AgroCares, announced a partnership for integrating trinamiX’s high-performance hardware into AgroCares’ next-generation nutrient scanner solution to next-generation solution for onsite nutrient analysis. TrinamiX is built on mobile NIR spectroscopy, combining robust hardware with flexible software to enhance onsite decision-making across various industries in on-the-spot nutrient testing.

Top Key Players

AI in Agriculture Market Share of Key Players

IBM John Deere Trimble AGCO Corporation GAMAYA PrecisionHawk VineView Vision Robotics Corporation INC. Farmers Edge Corteva Agriscience Microsoft Corporation Trace Genomics INC. Connecterra Harvest Croo. DeLaval Taranis

Frequently Asked Questions (FAQs)

How big is the AI in Agriculture Market?
The global AI in agriculture market was valued at USD 1000.25 million in 2022. It is projected to reach USD 5.96 billion by 2031, growing at a CAGR of 25% during the forecast period (2023–2031).
Asia-Pacific region has the highest growth rate in the AI in Agriculture Market.
Agricultural Labor Force is Steadily Decreasing are one of the key opportunities in AI in Agriculture Market.
Rising Need for Real-Time Livestock Monitoring are some key drivers supporting the growth of the AI in Agriculture Market.
The global AI in agriculture market is segmented by component, technology, and application.

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