The much-talked-about phenomenon in the global marketplace today is the role of artificial intelligence. AI has been responsible for fuelling a paradigm shift in operational efficiencies across most business sectors, including agriculture. Autonomous tractors, robots tending to crops, and drones precisely dispersing inputs are a big leap forward from 20th-century farms.
Taking a leaf out of the book of drones, agricultural drones are helping farmers increase crop production and monitor crop growth for maximum outputs. Farmers are using drone data to extract soil samples to check temperatures, moisture, and elevation.
Or let’s take a look at driverless tractors; they aim to release the farmers from 8-12-hour days of just driving. They allow farmers to take control via an app on their phone or computer. The farmer can use the app to position a tractor, drive the length of a field, turn around, come back, and maneuver around obstacles. Additionally, seed sowing requires a substantial amount of human effort and is time-consuming, but seed-sowing robots are saving farmers time and money. The autonomous devices plant seeds in the desired position, taking away the human element usually required.
According to the Mordor Intelligence Report, AI in the agriculture market is projected to register a CAGR of 4.24 percent over the next five years.
Artificial intelligence techniques for agriculture help boost productivity and yield. Consequently, agribusiness corporations adopt artificial intelligence technologies in terms of predictive analytics-based resolutions. AI-based applications and techniques can maximize crop yields, driving the market.
According to the United Nations (UN), the global population is projected to reach 9.8 billion by 2050. Limited arable land availability and the need for increased food production for food security drive a green revolution fuelled by the Internet of Things (IoT), artificial intelligence, and big data.
It is also important to note that an increase in the adoption of cattle face recognition technology is driving the market. By applying advanced metrics, including cattle facial recognition programs and image classification incorporated with body condition scores and feeding patterns, dairy farms can now monitor all behavioral aspects in a group of cattle individually.
One of the biggest drivers of AI in the agriculture sector is that the agriculture labor force has decreased in recent years due to the decreased interest in farming and the aging farmer population. As the population of farm laborers continues to decline, farmers are feeling pressure to keep up with production for the growing demand for fresh produce. Moreover, the downward trend of labor is translating into higher labor wages. A massive workforce decline is being observed worldwide for many reasons. A lack of skilled labor, aging farmers, and younger generations finding farming an unattractive profession contribute to this decline. Thus, encouraging trends for artificial intelligence in agriculture are increasing.
According to the Food and Agriculture Organization Corporate Statistical Database (FAOSTAT)(2017-20) report, the agriculture sector’s contribution to employment declined from 896.34 thousand people in 2017 to 873.75 thousand people in 2020.
Furthermore, the agricultural industry in the United States and the United Kingdom, among other countries, depend on laborers, and a similar trend is seen across other developed countries as well. On a similar note, Asia-Pacific, where agriculture occupies a significant part of the economy, is witnessing a massive decline in the workforce, nearly a decline of 618,147 thousand people in 2017 to 589,103 thousand people in 2020.
The labor shortage has become a global problem, with an aging farmer population that further limits the supply of manual labor. Thus, the decline in the agricultural workforce is encouraging governments and private organizations to focus on automating operations by adopting artificial intelligence technologies in the agricultural sector. Owing to the above factors, the market for artificial intelligence in the agricultural sector is likely to boom in the years to come.
In the 2022-23 budget speech, the government of India under the leadership of Prime Minister Narendra Modi recognized the potential of digital agriculture technology and innovation and announced that a Public-Private Partnership (PPP) scheme will be launched to scale these technologies. The Indian Government, during 2020-21 and 2021-22, has allocated funds to the tune of INR 1756.3 cores and INR 2422.7 crores to the States for introducing new technologies including drones, artificial intelligence, blockchain, remote sensing and GIS, etc in agriculture. Further, the Government also allocated INR 7302.50 crores and INR 7908.18 crores in 2020-21 and 2021-22 respectively to ICAR (Indian Agricultural Research Institute) for undertaking Research and Development in Agriculture for developing new technologies, their demonstration at farmer’s fields and capacity building of farmers for adoption of new technology.
The World Economic Forum’s Artificial Intelligence for Agriculture Innovation (AI4AI) initiative aims to transform the agriculture sector in India by promoting the use of artificial intelligence (AI) and other technologies. Through AI4AI, the Saagu Baagu pilot was launched in partnership with the Government of Telangana, making it the first Indian state to implement a framework for scaling up emerging technologies and improving productivity, efficiency, and sustainability in the agriculture sector. As of January 2023, more than 7,000 farmers have enrolled in the pilot project, with a focus on chili producers. These farmers are receiving support in the form of various AI technologies, including sowing quality testing, soil testing, crop health monitoring, window prediction, and tillage estimation, as well as accessing new customers and suppliers in different geographies.
There are reportedly more than 1,000 agri-tech startups in India offering a range of tech-based solutions, including digital finance, micro-insurance, access to agricultural inputs, quality testing, traceability, and market connect platforms. They have the potential to significantly contribute to improving productivity and sustainability, but fragmented technological infrastructure, high cost of operations, lack of access to data, and limited technical expertise, hamper the scale of these technologies. The need for more data collection and sharing standardization is restraining the market growth. Machine learning, artificial intelligence, and algorithm designs have advanced fast, but collecting well-tagged, meaningful agricultural data needs to catch up. This holds back the market’s growth during the forecast period.
One example of AI in agriculture is an AI-based chatbot developed by Digital Green in collaboration with ColoredCow. This chatbot uses AI to provide farmers with customized notifications and short videos on a real-time basis, helping them plan and manage their crops more efficiently. Another example is an AI-based food quality assessment technology developed by Agnext. This assessment machine simplifies the process of on-spot quality standardization as well as fostering economic, social, and ecological profits.
While India is one of the biggest agricultural technology (agritech) markets for equity investments with nearly USD 500 million invested in agritech start-ups in 2020-21, there is still unmet demand for commercial capital. A Bain and Company 2021 report estimates that the Indian agritech sector will attract USD 30-35 billion in investment by 2025. Blended finance structures, by pooling different risk-taking capital (capital that’s invested in high-risk, high-impact initiatives to demonstrate the feasibility of the initiative), can play a crucial role in kickstarting investments in the sector.
Globally spending on smart, connected agricultural technologies and systems, including AI and machine learning, is projected to triple in revenue by 2025, reaching USD 15.3 billion. IoT-enabled Agricultural (IoTAg) monitoring is smart, connected agriculture’s fastest-growing technology segment projected to reach USD 4.5 billion by 2025, according to PwC.
Artificial Intelligence in agriculture has been seeing a lot of direct application in farming. AI-powered solutions will not only enable farmers to do more with less, it will also improve quality and ensure faster go-to-market for crops.Advances in computer vision, mechatronics, artificial intelligence, and machine learning are enabling the development and deployment of remote sensing technologies to identify and manage plants, weeds, pests and diseases. Artificial intelligence solutions can enable farmers not to only reduce wastage, but also improve quality and ensure faster market access for the produce.
