## Amul Deploys AI to Empower India’s Dairy Farmers, Aiming for a “White Revolution 2.0”
In a move signaling AI’s potent reach beyond urban tech hubs, Amul, the world’s largest dairy cooperative, has launched an ambitious artificial intelligence initiative aimed at transforming the lives of millions of rural dairy farmers across India. Dubbed “Amul AI” and personified by its virtual assistant Sarlaben, the platform leverages five decades of accumulated cooperative data to provide personalized, round-the-clock guidance to farmers in their local languages.
This initiative, unveiled ahead of the AI Impact Summit 2026 and supported by India’s Ministry of Electronics and Information Technology (MeitY) along with the EkStep Foundation, represents a critical test case for AI’s ability to bridge the “last mile” gap in delivering technological benefits to underserved populations.
### Sarlaben: An AI Companion for Every Dairy Farmer
Sarlaben operates on one of India’s most extensive agricultural data repositories, accessible through the Amul Farmer mobile app, which has already seen over a million downloads, and via voice calls for those utilizing feature phones or landlines. The system is deeply integrated with Amul’s Automatic Milk Collection System (AMCS) and the Pashudhan application, enabling it to deliver tailored advice specific to individual cattle.
What sets Amul AI apart is the sheer scale and diversity of its training data. The platform is built upon a digital infrastructure that processes over two billion milk procurement transactions annually, encompasses veterinary treatment records from over 1,200 veterinarians covering nearly 30 million cattle, and includes data from approximately seven million artificial inseminations each year. Furthermore, it incorporates ISRO satellite imagery for fodder production mapping and utilizes data from a decennial cattle census.
Each animal within the system is assigned a unique identification, with detailed records tracking feed intake, medical history, and milking status. “Amul AI is about delivering dependable, verified information directly to the farmer – instantly and in a language they are comfortable with,” explained Jayen Mehta, Managing Director of the Gujarat Cooperative Milk Marketing Federation (GCMMF), which markets the Amul brand. By integrating decades of structured data with their operational systems, Mehta believes the platform will empower farmers to make informed, timely decisions that enhance animal productivity and, consequently, their income.
### India’s Productivity Paradox: High Volume, Low Yield
India stands as the world’s largest milk producer, with an estimated output of 347.87 million tonnes in 2024-25. However, despite this impressive volume, the country’s per-animal milk yield remains significantly lower than global averages. This disparity is attributed to systemic challenges, including small herd sizes, poor feed quality, limited access to veterinary services in rural areas, and a general lack of awareness regarding modern breeding and husbandry practices. Amul’s vast network, spanning over 18,600 villages in Gujarat and handling 35 million liters of milk daily, highlights the sheer scale of the challenge. Information asymmetry has long been a major hurdle, leaving farmers in remote areas with limited recourse for urgent animal care issues. Amul AI is strategically designed to bridge this critical information gap.
Initially available in Gujarati, the primary language of Amul’s farmer base, the platform is being developed on the government’s Bhashini multilingual framework. This foundation allows for potential expansion to all 20 major Indian languages, extending Amul’s reach across its presence in 20,000 villages nationwide.
### The Cooperative Model: A Foundation for Innovation
The success of Amul AI is intrinsically linked to its institutional framework. The cooperative structure, meticulously built over five decades during India’s original “White Revolution,” has provided the essential data infrastructure that underpins Amul AI. Unlike many private agri-tech startups that begin by collecting data and then developing products, Amul already possessed a rich, historical dataset. The crucial step was to develop a mechanism for making this data actionable at the farmer level.
Industry observers note the significance of this approach. Sreeshankar Nair, Founder of dairy-tech startup Brainwired, points out that Amul AI is well-positioned to address three key challenges: farmer education, access to quality veterinary guidance, and connectivity to grazing and feed resources. Nair believes that integrating local Indian dialects could indeed usher in a “White Revolution 2.0,” underscoring the transformative power of vernacular AI in a sector where linguistic diversity is a reality.
Saswata Narayan Biswas, Director of the Institute of Rural Management, Anand (IRMA), which has strong ties to Amul’s founding principles, frames Amul AI as an AI embedded within a cooperative structure. He views it not merely as a technological upgrade but as a powerful instrument for inclusive rural transformation. For Biswas, the advanced capabilities Amul AI offers—such as predictive disease detection, oestrus cycle tracking, optimized feed formulation, and localized weather risk advisories—are enhancements of services Amul has been developing for years, now accelerated and democratized by AI.
### Scaling Up and the Road Ahead
The initiative has garnered significant governmental support, with Gujarat Chief Minister Bhupendra Patel formally launching the platform and confirming its showcase at the AI Impact Summit 2026. Amul has recognized MeitY and the EkStep Foundation as key partners in developing the AI layer of the platform.
Even farmers not directly affiliated with Amul can access general dairy and animal husbandry information through the app. Currently, Amul AI covers nearly 30 million cattle, a number exceeding most national veterinary databases globally.
The paramount question, as with any large-scale AI deployment, is whether the tool will effectively reach and benefit those who need it most. Those farmers already comfortable with smartphones and integrated into Amul’s digital ecosystem are likely to be the first beneficiaries. The true measure of success will lie in the adoption rate among feature-phone users relying on voice interactions, the effectiveness of Bhashini-enabled dialect support, and, ultimately, whether AI-driven advisories translate into tangible improvements in milk yield.
Amul has constructed its AI system upon a bedrock of half a century of real-world cooperative transactions, animal data, and farmer interactions. This established infrastructure provides a credible foundation for scaling AI in dairy farming. The ultimate fulfillment of its promise will hinge on effective execution and the ability of Sarlaben’s guidance to penetrate the most remote and underserved communities, areas that have historically presented the greatest challenges in adoption and impact.
Original article, Author: Samuel Thompson. If you wish to reprint this article, please indicate the source:https://aicnbc.com/19158.html
