AI in Agriculture Market Size, COVID-19 Impact Analysis, Regional Outlook, Growth Potential, Competitive Market Share & Forecast, 2021 – 2027

Report ID: GMI2211




Summary Methodology

AI in Agriculture Market size is set to grow exponentially over 2021-2027. This is attributable to the significant role played by IoT sensors, AI and ML in agriculture to improve crop yields, increase agricultural efficiencies, and lower food production costs. Moreover, rising food demand, climate change, and labor costs are ushering in an era of machine modernization in the agricultural landscape.
 

Artificial intelligence in agriculture refers to the usage of innovative technologies to solve traditional farming problems. The agriculture industry has been leveraging AI technologies to improve a broad range of tasks in the entire supply chain, such as pest control and workload management.
 

Significant shift from traditional farming approaches to technologies like satellite remote sensing to monitor crop health will foster artificial intelligence (AI) in agriculture market trends. Furthermore, increasing investments in precision farming and the mounting adoption of AI technology among farmers to track crop humidity, temperature, and soil composition will contribute to the overall market outlook. Precision farming startup CropIn, for example, secured $20 million in funding from investors like ABC World Asia to drive growth across the global market.
 

Based on technology, the global AI in agriculture market from the predictive analytics segment is expected to register commendable revenue by 2027. This can be credited to the rising concerns regarding the impacts of plant diseases and pests on food availability and safety for human and animal consumption. Predictive analytics leverages AI to detect pests, diseases in plants, and poor plant nutrition, while improving agricultural accuracy through probabilistic models for seasonal forecasting.
 

From a regional perspective, the Europe artificial intelligence (AI) in agriculture market will hold a considerable share by 2027. This is due to the emergence of the UK as the global leader in the development of AI-based agriculture solutions. British agritech startup Small Robot Company, for example, introduced its commercial monitoring robot known as Tom in 2021, designed for use in various applications including regenerative farming.
 

The competitive landscape of the AI in agriculture market comprises companies such as Raven Industries, SciCorp, Grownetics, Agrosmart, Pycno, Hortau, aWhere, Gamaya, Granular (Corteva, DuPont), AGCO, Agworld, FarmLogs, Trimble, Iteris, and John Deere, among others. Strategic mergers and acquisitions and business expansions are the prominent initiatives being undertaken by these industry participants to reinforce their position across the global market.
 

For instance, John Deere announced the acquisition of Bear Flag Robotics in August 2021, with an objective to increase food production and reduce operational costs through machine automation.
 

In August 2021, Trimble introduced Trimble Ventures to set up $200 million funds and invest in early and growth-stage startups that lend a strong focus on technology-enabled innovation in industries including agriculture.

 

High prevalence of robotics in farming during COVID-19 to impact AI in agriculture market trends:

The novel coronavirus pandemic has posed massive challenges across various businesses, including the agriculture system. The pandemic has adversely impacted marketing and production through labor and logistical constraints, while the shock to financial stability restricted access to markets and led to increased food commodities prices.
 

However, the accelerated digitization of the farming sector driven by the pandemic may aid the recovery of artificial intelligence (AI) penetration in the agriculture industry. Farmers worldwide are increasingly focusing on automation and precision agriculture due to the challenges associated with using herbicides in crop production. The use of autonomous robots that are capable of mechanical weeding is also anticipated to offer farmers an attractive alternative to sustain their businesses during the outbreak.
 


What Information does this report contain?

Historical data coverage: 2016 to 2020; Growth Projections: 2021 to 2027.
Expert analysis: industry, governing, innovation and technological trends; factors impacting development; drawbacks, SWOT.
6-7 year performance forecasts: major segments covering applications, top products and geographies.
Competitive landscape reporting: market leaders and important players, competencies and capacities of these companies in terms of production as well as sustainability and prospects.


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