AI For Agriculture Market Size, Share, Opportunities, And Trends By Technology (Machine Learning, Computer Vision, Predictive Analytics), By Application (Agricultural Robots, Precision Farming, Drone Analytics, Livestock Monitoring, Weather Tracking, Others), And By Geography - Forecasts From 2023 To 2028

The AI For Agriculture Market size was valued at US$1,310.904 million in 2021 and is expected to grow at a CAGR of 24.84% to reach US$6,195.601 million by 2028.

Variables on temperature, soil, water use, weather, etc. are generated daily by farms. Artificial intelligence (AI) and machine learning models use this data in real-time to derive insightful conclusions, including when to plant seeds, which crops to select, which hybrid seeds to select for higher yields and other things. Precision farming also referred to as intelligent systems, is helping to improve the general value and precision of yields. AI helps to identify infestations, plant diseases, and malnourishment in farms. Before choosing which herbicide to apply in the region, artificial intelligence AI sensors can detect and target weeds. Many technical firms created robots that accurately monitor weeds with spray guns by using image processing techniques and artificial intelligence. These robots are capable of lowering the price of herbicides by eliminating large amounts of the chemicals that are often sprayed on crops. By dramatically reducing the number of pesticides required in the fields, these sophisticated AI sprayers can raise the standard of agricultural output.

The main market growth drivers for AI in agriculture are rising globalization,  implementation of new advanced technology, and increasing R&D investments by the government.

The market value is expected to further grow due to rising consumer demand for high-quality agricultural produce, encouraging government initiatives and regulations to encourage contemporary agricultural technologies and methods, and extensive industrialization. The market is also expected to expand as a result of rising costs for research and development efforts as well as an increase in the use of drones in agricultural operations. For instance, according to government reports, the Indian Government provided funds to the States for the introduction of new technologies such as drones, artificial intelligence, blockchains, remote sensing, and GIS in agriculture during the fiscal years 2020–21 and 2021–22 totalling approximately US$212.2 million and US$292.7 million, respectively. According to the same report, the government also provided ICAR (Indian Agricultural Research Institute) with US$882.3 million and US$955.5 million in 2020–2021 and 2021–2022 respectively for undertaking research and development in agriculture for developing new technologies, their demonstration on farmer's fields, and building farmers' capacity for adopting new technologies.

Market expansion is constrained by a lack of technological competence and understanding in developing countries along with high expenses.

The market's growth rate is slowed down by technological difficulties, interoperability problems, and a lack of standards. The AI in agriculture market growth rate is further hampered by significant technology restrictions in less developed nations and by the high expenses involved in collecting precise field data. Furthermore, there is a severe shortage of data sharing, and although machine learning, artificial intelligence, and advanced algorithm design have evolved significantly, the collection of useful and well-tagged agricultural data has stalled far behind.

Key Developments.

• In December 2022, Google revealed a US$1 million contribution to IIT Madras for the establishment of a multidisciplinary centre for responsible artificial intelligence. This centre would examine and investigate many facets of bias in AI with an emphasis on the Indian context. The tech giant will also give a comparable sum to independent non-profit Wadhwani AI in order to create AI models that would assist track crop diseases, forecast yields, and improve call centres for farmers. The business also said at the Google for India 2022 event that it will contribute to the agro stack as defined by the Indian government by combining AI and remote sensing to more effectively handle the issues that arise in agriculture.
• At a ceremony held at the International Center for Biosaline Agriculture's offices in December 2022, the UAE Minister of Climate Change and the Environment revealed a new AI-powered mobile application for detecting crop problems (ICBA). The program was developed with the help of regional partners in Egypt, Tunisia, and the United Arab Emirates to help smallholder farmers and extension specialists identify crop abnormalities early on, minimizing output losses and raising revenues. It can recognize 18 distinct prevalent diseases that harm cucumber, tomato, and capsicum. 

Europe and North America are expected to acquire significant shares in the AI for Agriculture market.

North America holds a significant share in the market for AI in agriculture due to the widespread use of cutting-edge farming technologies to produce the highest levels of output. Additionally, large firms are providing services to local consumers through collaborations with other top players.

Further, agriculture is a major industry in Europe since farmers manage over half of the continent's land area. The use of computer vision and artificial intelligence in monitoring and reporting tools for indoor and outdoor farms as well as in providing a visual representation of the farmer's full output is growing the AI market in agriculture in Europe.

In contrast, the Asia Pacific regional market is anticipated to develop the fastest during the next few years. This may be a result of the rapidly growing usage of smart agricultural techniques including precision farming, agronomic robots, and drone analytics. China has been a big contributor to the Asia Pacific industry as a result of the country's quick adoption of cutting-edge methods in its extensive agriculture sector.

AI For Agriculture Market Scope:

Key Market Segments

• By Technology
  • Machine Learning
  • Computer Vision
  • Predictive Analytics
• By Application
  • Agricultural Robots
  • Precision Farming
  • Drone Analytics
  • Livestock Monitoring
  • Weather Tracking
  • Others
• By Geography
  • North America
    • USA
    • Canada
    • Mexico
  • South America
    • Brazil
    • Argentina
    • Others
  • Europe
    • Germany
    • France
    • United Kingdom
    • Spain
    • Others
  • Middle East And Africa
    • Saudi Arabia
    • Israel
    • UAE
    • Other
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Indonesia
    • Vietnam
    • Thailand
    • Others