Although artificial intelligence technology has led to excitement in the whole industry, for agricultural AI players to quickly adopt the same and survive in the market, understanding the driving and restraint factors of the market is crucial.
Artificial intelligence technology brings the concept of cognitive computing to agriculture, where the farm equipment intelligence is modeled on human intelligence. Artificial intelligence technologies help farmers in optimizing their planning to generate profitable crop yields using predictable analytics for agricultural input choices and farm process planning.
The capabilities enabled by this technology allow the farm equipment and solutions to interpret, acquire, and react to unpredictable farm situations with enhanced efficiency.
Since 2010, the adoption of artificial intelligence in agriculture solutions has increased, especially by medium and large-scale farmers. Increased awareness regarding the benefits of these solutions has increased the adoption rate of these solutions. High technological advancement in some regions of the world is another driver toward the adoption of artificial intelligence in agriculture solutions by farmers.
Precision agriculture encompasses several technologies such as guidance technologies, sensing technologies, analytics, and other precision technologies that reduce the misutilization of agri-inputs and enable efficient farming with profitability. The introduction of precision agriculture technologies has also resulted in the creation of hundreds of thousands of data points on farms. The rise in these data points has enabled data-driven farming, aiding the growers and consumers of agriculture products with insight-backed decision-making. However, the abundance of these data points has also left the agriculture industry plagued with massive amounts of data. To navigate through these big data in farms and to attain efficient farming solutions, the industry is bringing about significant product innovations in farm data analysis using artificial intelligence technology.
Artificial intelligence technology brings the concept of cognitive computing to agriculture, where the farm equipment intelligence is modeled on human intelligence. The capabilities enabled by this technology allow the farm equipment and solutions to interpret, acquire, and react to unpredictable farm situations with enhanced efficiency. Artificial intelligence technologies help farmers in optimizing their planning to generate profitable crop yields using predictable analytics for agri-input choices and farm process planning. For instance, AI technology has found use cases in crop disease detection, crop growth assessment, and crop yield prediction, preventing the over-application of fertilizers and other agri-inputs. The forecast of results for these agricultural processes in the market is powered by AI sensors and imaging equipment. The presence of these AI-based software and hardware products and services in the agriculture market has led to an optimistic growth of the precision agriculture market.
Although artificial intelligence technology has led to excitement in the whole industry, for agricultural AI players to quickly adopt the same and survive in the market, understanding the driving and restraint factors of the market is crucial.
The global artificial intelligence in agriculture market is expected to reach $6,655.1 million by 2026, with a CAGR of 30.56% during the forecast period 2021-2026. The growth rate in the market is because of the increased awareness of artificial intelligence-based solutions in some regions of the world.
There are certain challenges that prove to be a restraint in the growth of global artificial intelligence in agriculture market. The awareness and knowledge about newer technological advancements in the agriculture technologies such as artificial intelligence are yet to spread extensively amongst the growers, especially amongst those of the emerging countries. The lack of technical infrastructure in agriculture of developing countries and data privacy concerns among growers also act as a restraint in the market. Find out everything about the topic in Artificial Intelligence in Agriculture Market Report made by Bis Research.
North America Leading the Global Artificial Intelligence in Agriculture Market:
The governing trends of artificial intelligence in agriculture market vary across different regions. Artificial intelligence in agriculture industry holds a prominent share in various countries of North America, Europe, Asia-Pacific (APAC), and Rest-of-the-World (RoW), including the U.K. and China.
The supply chain for the majority of the industries across the globe got impacted due to the COVID-19 pandemic, including the artificial intelligence in agriculture industry. During the COVID-19 outbreak, the supply chain of the agriculture industry was disrupted. During the COVID-19 pandemic, agricultural production was hindered for farmers, which led to a decrease in their revenue generation. This has left the farmers in no position to invest in modern agricultural equipment.4
Key Questions Answered in the Report
• What is the estimated global artificial intelligence in agriculture market size in terms of revenue for the forecast period 2021-2026, and what is the expected compound annual growth rate (CAGR) during the forecast period 2021-2026?
• What are the key market drivers, and opportunities in the market pertaining to artificial intelligence in agriculture?
• What are the Artificial Intelligence in Agriculture Market Trends?
• What are the major restraints inhibiting the growth of global AI in agriculture market?
• What kinds of new strategies are being adopted by the existing market players to strengthen their market position in the industry?
• What is the competitive strength of the key players in the artificial intelligence in agriculture market based on an analysis of their recent developments, product offerings, and regional presence?
• How is the competitive benchmarking of the key artificial intelligence in agriculture companies in the agriculture market based on the analysis of their market coverage and market potential?
• How much revenue is each segment expected to record during the forecast period, along with the growth percentage?
• What is the type of players and stakeholders operating in the market ecosystem of artificial intelligence in agriculture, and what is their significance in the global market?
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