Artificial Intelligence in Agriculture Market

Global Artificial Intelligence in Agriculture Market Size & Growth Rate ( 2022 - 2027 )

The Global Artificial Intelligence in Agriculture Market has been valued at US$ 1.52 Billion in 2022 and it is expected to reach the high market capital of US$ 5.24 Billion by 2027. During this forecast period it is anticipated to grow with the healthy CAGR of 26.35% over 2022-2027.

Global Artificial Intelligence in Agriculture Market Overview:

Farming approaches that use artificial intelligence can assist enhance production and yield. In the entire food supply chain, AI-based apps and approaches help control pests, yield healthier crops, monitor the soil, and optimise agriculture-related jobs. Because AI aids in the analysis of agricultural data, artificial intelligence is rapidly being used in the agriculture business to increase harvest quality and accuracy. The expansion of artificial intelligence (AI) in agriculture is attributed to a growing focus on technological advancements by major companies, rising upgradation of current infrastructure with advanced technologies, and rising use of artificial intelligence, particularly in developing nations.

The market is being driven by the desire to maximise crop productivity utilising machine learning techniques. Species selection is a time-consuming process of looking for specific genes that determine the efficiency of water and nutrient consumption, climate change adaptation, disease resistance, nutrient content, and taste. Machine learning algorithms, specifically deep learning algorithms, examine decades of field data to analyse crop performance in various climates and develop a probability model based on this data to forecast which genes will most likely contribute a favourable characteristic to a plant.

Global Artificial Intelligence in Agriculture Market Drivers & Restraints:

Drivers:

Rising globalisation and the agricultural industry's adoption of new advanced technologies will emerge as the primary market growth drivers. The market value will be further aggravated by rising demand for high-quality agricultural products, supportive government policies and measures to encourage advanced agricultural tools and practises, and growing industrialisation. Increased spending on research and development, as well as an increase in the use of drones in agricultural farms, will help to propel the market forward.

The market is being driven by an increase in the deployment of cattle facial recognition technology. Dairy farms can now individually monitor all behavioural features in a group of cattle using advanced metrics such as bovine facial recognition systems and image classification coupled with body condition score and feeding habits. The use of drones in agriculture can be used in crop field scanning with small multispectral imaging sensors, GPS map production with onboard cameras, heavy payload delivery, and livestock monitoring with thermal-imaging camera-equipped drones, which is boosting the market.

Restraints:

However, market growth is being stifled by a lack of standardisation in data collection and data sharing. Machine learning, artificial intelligence, and advanced algorithm design have grown at breakneck speed, but the collection of well-tagged, valuable agricultural data has lagged far behind. However, the market's expansion will be limited by a lack of knowledge and technological expertise. The market's growth pace will be slowed further by technological obstacles, interoperability issues, and a lack of standardisation. The market growth rate would be further hampered by large-scale technological restrictions in developing economies and high expenses associated with precision field data collection.

Recent Developments in Global Artificial Intelligence in Agriculture Market:

AI, quantum, and design technology are now part of the Radical Collaboration programme. Collaborative research, like hourly chimes, Big Red hockey, and Slope Day, is an integral part of life at Cornell. It's a commitment that the university takes very seriously, and it's growing now.

NEC Laboratories, a division of NEC Corporation India, said that it has inked a memorandum of understanding (MOU) with Tamil Nadu Agricultural University (TNAU) to provide artificial intelligence (AI) and machine learning-based solutions for early disease identification in crops. According to a release, NEC seeks to help identify illness and deficiency categories, as well as give cures through agricultural experts, under the terms of the MoU.

Global Artificial Intelligence in Agriculture Market Segmentation:

By Technology:

• Machine Learning.
• Computer vision.
• Predictive Analytics.

Predictive Analytics is expected to have the dominant share in the Global Artificial Intelligence in Agriculture Market During the Forecast Period. Pesticide control, weed management, irrigation and drainage management, weather surveillance, and crop disease infestations are all key difficulties for the agriculture industry. Using image analysis and neural networks, predictive analysis aids farmers in analysing and addressing these issues. Artificial intelligence will be deployed through predictive analytics. Ag Eagle Aerial Systems Inc., Microsoft, and Granular, Inc., for example, collaborated on a prediction-based analytics technology to produce AI-enabled farming and agriculture solutions and platforms.

By Offering:

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

Software is expected to have the dominant share in the Global Artificial Intelligence in Agriculture Market During the Forecast Period. However, market growth is being stifled by a lack of standardisation in data collection and data sharing. Machine learning, artificial intelligence, and advanced algorithm design have grown at breakneck speed, but the collection of well-tagged, valuable agricultural data has lagged far behind. However, the market's expansion will be limited by a lack of knowledge and technological expertise. The market's growth pace will be slowed further by technological obstacles, interoperability issues, and a lack of standardisation. The market growth rate would be further hampered by large-scale technological restrictions in developing economies and high expenses associated with precision field data collection. The benefits of AI-enabled software for potential application areas such as precision farming and drone analytics are fuelling the AI in agriculture market's software segment's rise.

By Application:

• Precision Farming.
• Drone Farming.

Precision Farming is expected to have the dominant share in the Global Artificial Intelligence in Agriculture Market During the Forecast Period. Precision farming is one of the most rapidly increasing AI-enabled agricultural applications. It aids farmers in reducing expenses and properly utilising resources. AI is used in precision farming to gather, interpret, and analyse digital data. For example, GPS-enabled combine harvesters use artificial intelligence to track harvest yields in order to analyse field variability, such as variances in water, soil makeup, or fungus, and create georeferenced data. Farmers can tailor fertilisers or insecticides based on the results of the analysis and projections. Agriculture robots operated by artificial intelligence integrate artificial intelligence, field sensors, and data analytics, and can be utilised for a wide range of tasks. Because they can weed and hoe, these robots are efficient harvesting devices. The agriculture robots’ market is driven by increasing adoption of artificial intelligence in agriculture and new robotics advances.

Global Artificial Intelligence in Agriculture Market Regional Analysis:

• Europe is expected to have the dominant share in the Global Artificial Intelligence in Agriculture Market During the Forecast Period. The European Soil Data Centre (ESDAC) is Europe's thematic centre for soil-related data, with the goal of serving as a single point of reference and hosting all important soil data and information at the European level. The 'Internet of the Soil,' a software and hardware system for monitoring soil parameters such as humidity, temperature, electrical conductivity, and more in European countries, is managed by AI corporations. Their sensors communicate wirelessly with a cloud-based platform that can be accessed from any device with an internet connection.
• North-America is expected to have the next dominant share in the Global Artificial Intelligence in Agriculture Market During the Forecast Period. as a result of the region's strong industrial automation industry and adoption of artificial intelligence technologies North America is characterised by increased population purchasing power, ongoing automation initiatives, significant IIoT investments, and increased government concentration on in-house AI equipment production. Numerous agricultural technology vendors are also investigating artificial intelligence solutions, which benefits the market.
• Asia-Pacific is expected to register the highest CAGR in the Global Artificial Intelligence in Agriculture Market During the Forecast Period. Its growth can be ascribed to the growing use of artificial intelligence in agriculture. In the food industry, emerging economies such as India and China are adopting artificial intelligence technologies such as remote monitoring technology and predictive analysis. Furthermore, in these economies, the growing need for smart cities is prompting agriculture enterprises to implement AI-based products and services.
• Latin-America.
• Middle-East and Africa.

Key Players in Global Artificial Intelligence in Agriculture Market:

• International Business Machines Corp.
• Deere & Company
• Microsoft Corporation
• Farmers Edge Inc.
• The Climate Corporation
• Descartes Labs
• Ag Eagle Aerial Systems