Artificial Intelligence in Agriculture Market Will Generate Massive Revenue by 2024

Global agriculture industry has undergone significant and dynamic changes in the past decades, specifically with the introduction of technologies introduced to improve crop yield. With the increase in world population leading to the rise in the global demand for food, growers are prompted to adopt the most advanced and productive methods in farming operations to increase crop yield. One of new-age methods applied for increase in production is the new efficient mode of farming known as precision agriculture. This way of farming has resulted in creation of large number of data points leading to the growth of data-driven farming. Consequently, the growers and consumers of agricultural products are left with complex big data to analyze. The analysis for this data  has prompted the need for cognitive computing with human-like intelligence in farm equipment and solutions based on such computing to yield healthier crops, as well as to monitor crops and soil conditions, control weeds, aid with farm workload, optimize data for growers, and enhance the farm operation efficiency. The set of cognitive computing technologies introduced in agriculture for the said purpose is known as artificial intelligence technology.

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. 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 the 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 over-application of fertilizers and other agri-inputs. The forecast of results for these agricultural processes in the market are 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.

Originally, artificial intelligence in the agriculture industry had been offered as a software platform. However, since past three years, a new pricing model and mode of product offering has emerged where the solution providers are billing the customers on the amount of artificial intelligence capability used including AI-based hardware and software. This pricing and business model are popularly termed as AI-as-a-Service (AIaaS). Presently, the AI companies in agriculture also offer support services as product offerings.

Agriculture technologies are offered for a host of agriculture applications and cover the entire farming cycle including data management, soil management, yield mapping, as well as monitoring, spraying, harvesting, and planting, among others. Adoption of agriculture technologies across the globe has resulted into the rapid accumulation of a large amount of agricultural data on farm operations and fields. Management of this big data for increased accuracy, productivity, and reduced manual data feeding has become a pressing requirement. Hence, the advent of artificial intelligence in the agriculture sector is welcomed by the growers and other agriculture customers, as AI technology has been critically used to optimize agricultural operations based on this data and has found innovative use cases and applications. Predictive analytics is one of the most deployed use cases of AI in agriculture, where it aids in efficient farm production with reduced losses.