How AI is Boosting Farming in India
India, hailed as a global agricultural powerhouse for being a leading producer and exporter of food, faces a flip side: its small-scale farms teeter on the brink of survival.
During the World Economic Forum (WEF), the current predicament of such farmers was described as "financial desperation". This characterization came from Jeremy Jurgens, Managing Director of the World Economic Forum, and Purushottam Kaushik Head of the Centre for the Fourth Industrial Revolution, World Economic Forum.
For context: India boasts 125 million small agricultural enterprises facing the constant challenge of balancing amidst high weather risks and resource scarcity. The WEF shares alarming statistics: thousands of these producers, overwhelmed by their troubles, have ended their lives.
Krishna exemplifies the plight of these farmers, a farmer diligently cultivating his 0.5-hectare plot in Telangana. For this, he earns $120 monthly, barely sufficient for his family’s sustenance. “But Krishna must also contend with unpredictable monsoons, frequent droughts, pest infestations, and diminishing yields,” WEF experts disclose.
Added to natural calamities are financial hurdles – small Indian agrarians lack easy access to modern banking services. Krishna is compelled to seek help from local lenders with exorbitant interest rates, making necessary seeds, fertilizers, or pesticides often unaffordable.
Furthermore, after overcoming all odds to harvest, about 40% of their revenue is invested in logistics – storage and transportation of produce, as market access demands that vegetables meet strict quality standards.
Jurgens and Kaushik observe that such farms are caught in the so-called trap of subsistence farming. Insufficient income prevents Indian farmers from investing needed amounts into their enterprises. Problems escalate annually, with investment levels continually diminishing. Price fluctuations in the market further worsen the situation: a single season of low buying prices can doom dozens of Indian micro-farms.
New technologies, such as precision agriculture, access to digital markets or drones, remain out of reach for most farmers like Krishna,aid WEF experts.
Thus, a year and a half ago, globalists decided to extend aid to Indian farmers, offering them the advantages of artificial intelligence. The Indian Centre for the Fourth Industrial Revolution, in partnership with India's Ministry of Agriculture and the state of Telangana, initiated the AI4AI (AI for Agriculture Innovation) program.
This pilot program established an ecosystem of farms, food processing entities, machinery manufacturers for the food industry, and more. Banks and insurance firms provided financial support, while a consortium of technology companies led the innovation efforts. AI aimed to facilitate interactions among these entities and boost the business efficiency of the weakest link – the mini-farms. The project ultimately encompassed about 7,000 farms in the Khammam district of Telangana.
The initiative has transformed chilli farming in Khammam district through bot advisory services, soil testing technology, AI-powered quality testing and a digital platform to connect buyers and sellers,WEF specialists report.
During this time, farmers harvested three crops. The financial results were encouraging: AI consultations helped increase chili pepper yields by approximately 21% per acre. Additionally, there was a noticeable reduction in the usage of expensive pesticides (down 9%) and fertilizers (down 8%). While individually modest, these figures combined to produce a significant cumulative effect
During this time, farmers reported a significant increase in net income: $800 per acre per crop cycle (6 months), effectively double the average incomeaccording to the WEF.
Therefore, the concept of rescuing Indian micro-farms through artificial intelligence has proven itself fully viable. The project is expected to expand to other states.
Previously, we reported that billionaire and visionary Bill Gates has forecasted that developing countries will achieve broad AI adoption by 2027.
