Artificial Intelligence Ai In Agriculture Market

According to Stratistics MRC, the Global Artificial Intelligence (AI) in Agriculture Market is accounted for $2.1 billion in 2023 and is expected to reach $7.9 billion by 2030 growing at a CAGR of 21.1% during the forecast period. Artificial intelligence is the study of the science and engineering involved in creating intelligent computer systems capable of simulating or displaying natural intelligence (human intelligence) and performing tasks like analysis, judgment, and decision-making without the need for human intervention. The agricultural industry has been transformed by artificial intelligence (AI), which has completely changed the ways farming and associated tasks are carried out. To tackle these issues and realize agriculture's full potential, AI technologies like machine learning, computer vision, and data analytics are being used. Beyond standard farming methods, AI in agriculture enables farmers and agricultural stakeholders to use data-driven insights and intelligent decision-making to improve production, optimize resource use, and handle numerous agronomic concerns.

According to UN Food and Agriculture Organization, the population will rise by 9.8 billion by 2050.



Market Dynamics:

Driver:

Growing food demand and population

The demand for food production is rising as the world's population expands. With the help of AI technologies, farmers can increase agricultural yields and maximize resource use to sustainably satisfy rising food demand. For instance, there were 8.0 billion people on earth in mid-November 2022. From the current 8 billion to 9.7 billion in 2050, the estimated increase in world population is around 2 billion people. A growing population increases the need for crops to produce more rapidly, yet AI can slow down agricultural activity in a number of different ways.

Restraint:

Unskilled labor and high cost

The high initial cost of implementation is an important obstacle to the growth of this sector. According to the requirements, low-income households in rural areas, among others, believe the cost of smart agriculture to be an insurmountable barrier, which prevents the widespread adoption of such cutting-edge equipment. However, due to land fragmentation and expensive beginning costs, there is no standardization of the massive amount of cumulative data, which causes an inefficient distribution of resources and severely restricts market expansion over the course of the analysis period.

Opportunity:

Government initiatives promoting the use of AI to manage small farms

There are more than 570 million farms around the globe, and 95 percent of these are smaller than 5 hectares. The majority of farms with more than 100 hectares of land use AI technology. This is demonstrated by the substantial initial outlay needed to develop AI systems. In general, farmers with land holdings larger than 100 hectares are able to invest in AI-based solutions for farm management and other uses. However, there is a chance for solution providers to concentrate on farms with fewer than 5 hectares of land because governments all over the world support the use of AI for agricultural applications and give aid to farmers with small farms.

Threat:

Limitations of large-scale technology in developing economies

Artificial intelligence and other Fourth Industrial Revolution-related technologies enable the automation of a wide range of processes in increasingly interactive and complex ways. By improving food production, for instance, these developments are expected to generate several prospects for economic and social development in underdeveloped nations. They could reinforce and amplify already existing disparities within developing nations and between those nations and more developed regions.

Covid-19 Impact:

The rapid COVID-19 pandemic breakout prompted the adoption of strict lockdown laws across a number of countries, which temporarily halted a number of agricultural activities and had a detrimental effect on the worldwide market for AI in agriculture. The epidemic has brought to light the necessity for agriculture automation to maintain the food supply and reduce human error. Global supply networks have been affected by COVID-19, which has an impact on the accessibility of agricultural supplies like fertilizer, pesticides, and machinery. Due to this disturbance, waste reduction and manufacturing efficiency optimization are again prioritized.

The software segment is expected to be the largest during the forecast period

Due to its ease of integration into agricultural machinery, labor cost savings, and real-time data collection, the software segment held the largest market share over the forecast period. Moreover, together with the use of analytical tools, the large amount of data being generated and stored in the cloud helps the farmer identify and manage every aspect of farming. The use of the program substantially improves farmers' capacity to adapt to shifting demands.

The predictive analytics segment is expected to have the highest CAGR during the forecast period

Predictive Analytics segment is estimated to witness lucrative growth throughout the extrapolated period. A branch of AI called predictive analytics uses historical data, machine learning algorithms, and statistical methods to forecast upcoming events or outcomes. Furthermore, predictive analytics is playing an increasing role in agriculture, assisting farmers to improve their operations, make informed decisions, and reduce risks. Models for predictive analytics examine past information on crop yields, weather patterns, the condition of the soil, and other important variables.

Region with largest share:

Due to the increased demand from emerging nations like China and India, Asia-Pacific held the largest portion during the projection period. The market for artificial intelligence in agriculture is predicted to be driven by the growing use of mechanical technology and IoT devices in agriculture. The wide variety of cutting-edge developments and products in the agriculture sector are associated with driving the market's expansion. Additionally, the region's AI agriculture industry is being driven primarily by population growth, climate change, and shortages of water. The market's growth in this region will be fueled by factors including rising automation, technological advancements like AI and ML, and decreasing soil quality.

Region with highest CAGR:

Owing to the adoption of AI technology by farmers and agricultural businesses in North America to boost productivity, improve resource allocation, and strengthen decision-making processes, North America is predicted to experience lucrative growth over the extrapolated period. Moreover, a few of the agricultural applications of AI in the area include automated farming systems, remote sensing, crop monitoring, and precision agriculture. With the help of modern technology, farmers may improve yields, minimize expenses, reduce risks, and make data-driven decisions.



Key players in the market

Some of the key players in Artificial Intelligence (AI) in Agriculture market include aWhere Inc., Cainthus Corp, Climate LLC (The Climate Corporation), Corteva, Descartes Labs, Inc, Gamaya, Granular Inc., IBM Corporation, Microsoft Corporation , PrecisionHawk Inc, Taranis and Valmont Industries (Prospera Technologies).

Key Developments:

In 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 U.S.

In October 2022, Microsoft announced, FarmVibes open-sourced by Microsoft Research.AI, a collection of machine-learning models and technologies for sustainable agriculture. FarmVibes. AI comprises data processing methods for merging spatiotemporal and geographic data, such as weather data and satellite and drone footage.

Offerings Covered:
• Service
• Software
• Hardware
• Other Offerings

Technologies Covered:
• Predictive Analytics
• Computer Vision
• Machine Learning
• Other Technologies

Applications Covered:
• Agriculture Robots
• Drone Analytics
• Labor Management
• Livestock Monitoring
• Precision Farming
• Fish Farming Management
• Smart Greenhouse Management
• Soil Management
• Intelligent Spraying
• Automatic Weeding
• Plantix app
• Other Applications

Regions Covered:
• North America
o US
o Canada
o Mexico
• Europe
o Germany
o UK
o Italy
o France
o Spain
o Rest of Europe
• Asia Pacific
o Japan
o China
o India
o Australia
o New Zealand
o South Korea
o Rest of Asia Pacific
• South America
o Argentina
o Brazil
o Chile
o Rest of South America
• Middle East & Africa
o Saudi Arabia
o UAE
o Qatar
o South Africa
o Rest of Middle East & Africa

What our report offers:
- Market share assessments for the regional and country-level segments
- Strategic recommendations for the new entrants
- Covers Market data for the years 2021, 2022, 2023, 2026, and 2030
- Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
- Strategic recommendations in key business segments based on the market estimations
- Competitive landscaping mapping the key common trends
- Company profiling with detailed strategies, financials, and recent developments
- Supply chain trends mapping the latest technological advancements

Free Customization Offerings:
All the customers of this report will be entitled to receive one of the following free customization options:
• Company Profiling
o Comprehensive profiling of additional market players (up to 3)
o SWOT Analysis of key players (up to 3)
• Regional Segmentation
o Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
• Competitive Benchmarking
Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances