How AI in Indian Agriculture Is Revolutionizing Its Poorest Regions
India is a nation with immense economic potential. In 2021, the World Bank ranked the nation first among the world’s seven largest emerging market and developing economies (EMDEs). India boasts an economy expected to grow by 7% in 2023. Despite this, its agricultural sector has struggled to keep up with the productivity levels in other comparable nations. A host of persistent structural issues inhibit irrigation, communication and a general understanding of crops.
AI, however, is increasingly helping innovate India’s agricultural economy. With the promise of abundant near-future investment, it could hold the key to a breakthrough in Indian agriculture. This, in turn, could yield a breakthrough in the battle against poverty.
The Importance of Agriculture to India’s Economy
For India, agriculture is key to its socioeconomic welfare. It is crucial to both its economy and food security, employing some 200 million people. The industry makes up 18% of the gross domestic product (GDP) and 40% of the total rural net domestic product.
General poverty rates in India have halved between 2006 and 2016, but India’s agricultural system suffers from acute structural issues. It is markedly behind the worldwide average in key areas, such as yield productivity in essential crops, water availability and market access.
These issues depreciate farm incomes and significantly worsen livelihoods, ultimately increasing indigence. India, however, finds itself at an inflection point, at which new technologies are showing the potential to galvanize productivity and alleviate poverty.
How AI is Causing Positive Change
In recent years, breakthroughs in artificial intelligence have allowed farmers to better understand their land, soil and crop health as well as neighboring environments. Two teams at Google are leveraging AI in Indian agriculture in order to develop a “unified ‘landscape understanding.” The AI works by employing satellite imagery and machine learning to draw boundaries between fields, crucial to forming meaningful calculations. Following this, the AI can determine the acreage of farm fields, as well as irrigation structures like farm wells which can help create tools for drought preparedness. This can also help calculate previous water availability over the past month, three months or year, all critical in establishing water security and drought management strategies.
Another promising advance for AI in Indian agriculture has come from the World Economic Forum’s Artificial Intelligence for Agriculture Innovation (AI4AI). This is led by the Centre for the Fourth Industrial Revolution (C4IR) India. By promoting the use of artificial intelligence, the AI4AI aims to “bring… together government, academia and business representatives” to develop innovative solutions for the agricultural sector. As of January 2023, 7,000 farmers, primarily chili producers, have been using the technology to monitor their crops. They also use it to perform quality control and test soil, which helps them access new customers in different regions.
An Even Brighter Future
The positive effects of AI in Indian agriculture have two dimensions. For farmers today, the accurate understanding of field performance and environmental conditions it provides allows them to reduce land and water waste while increasing crop yield. Yet, even more promising is the potential benefits it could bring to future farmers. As more information is gathered on farm performance, agricultural loans will become more available. This will allow state governments to provide increasing support for farming districts at scale. AI in Indian agriculture, led by companies such as Google, will support its rapidly growing technology industry. New artificial machinery is also increasingly undergoing development to make farming practices more efficient and sustainable.
Domestic investment indicates a positive future. At present, there are more than 1,000 agri-tech startups in India. They offer a range of services, including digital finance, quality testing and market connect platforms. As agri-tech develops, these businesses should exponentially increase agriculture productivity and sustainability, improving food security for some of India’s poorest people.
Some Challenges AI May Face in Agriculture
Though AI presents a very exciting prospect for Indian agriculture, it is not free of potential challenges. Foremost among these is the fact that AI systems require a great deal of data to train machines and make accurate predictions. For large agricultural areas, learning models would take time to mature. Though solutions are emerging, there may be a significant delay until farmers can reap their full benefits.
Nonetheless, recent developments of AI in Indian agriculture herald a fundamental change in productivity that should continue revolutionizing the yield, communication and water access of farmers over the coming years, and perhaps even decades. This will provide vital economic assistance to India’s farmers, many of which live below the extreme poverty line, and crucially stabilize food security to help feed the country’s 1.4 billion people.
– Gabriel Gathercole