Amul, the world's largest dairy cooperative, has launched an ambitious AI initiative named Amul AI, deploying an AI assistant called Sarlaben to serve 36 lakh (3.6 million) women milk producers in the villages of Gujarat, India. This platform, built on five decades of the cooperative's extensive data, aims to provide round-the-clock, personalized guidance to every farmer in their own language. Positioned as a critical test case for AI's ability to reach the 'last mile,' Amul AI was launched ahead of India's AI Impact Summit 2026 and is supported by the Ministry of Electronics and Information Technology (MeitY) and the EkStep Foundation.

Sarlaben leverages one of India's most comprehensive agricultural data repositories. Farmers can access the assistant through the Amul Farmer mobile app, which has already garnered over one million downloads on Android and iOS. For those using feature phones or landlines, Sarlaben is accessible via voice calls. The system is deeply integrated with Amul’s Automatic Milk Collection System (AMCS) and the Pashudhan application, enabling it to deliver tailored, cattle-specific advice.

What sets Amul AI apart is the monumental scale of its training data. The platform's digital backbone manages over 200 crore (two billion) milk procurement transactions annually. It incorporates veterinary treatment records from more than 1,200 doctors covering nearly 3 crore (30 million) cattle, approximately 70 lakh (seven million) artificial inseminations conducted each year, ISRO satellite imagery for fodder production mapping, and a cattle census conducted every five years. Crucially, every animal within the system is assigned a unique ID, with individual records detailing feed intake, disease history, and milking status.

Jayen Mehta, Managing Director of the Gujarat Cooperative Milk Marketing Federation (GCMMF), which markets the Amul brand, emphasized that "Amul AI is about taking dependable, verified information directly to the farmer – instantly and in a language they are comfortable with." He highlighted that by leveraging decades of structured data and integrating it with operational systems, the platform will empower farmers to make timely decisions that boost animal productivity and income.

Despite being the world’s largest producer of milk, generating 347.87 million tonnes in 2024-25, India faces a significant productivity paradox: its per-animal milk yield remains among the lowest globally. This is attributed to structural challenges such as small herd sizes, low-quality feed, limited access to veterinary care in rural areas, and a widespread lack of awareness regarding modern breeding and husbandry practices. Amul's network, spanning over 18,600 villages in Gujarat, handles more than 350 lakh litres (35 million litres) of milk daily, but information asymmetry has long been a bottleneck. Amul AI is designed to bridge this gap, especially for farmers in remote areas facing challenges like a sick animal at midnight.

Initially available in Gujarati, the primary language of Amul’s farmer base, the platform is built on the government’s Bhashini multilingual framework. In principle, it can be extended to 20 Indian languages, potentially reaching Amul’s presence in 20,000 villages across 20 states.

The institutional foundation of Amul’s cooperative structure, built over five decades during the original White Revolution, is integral to Amul AI's success, as it provided the data infrastructure necessary for such a platform. Unlike many agri-tech startups that collect data first, Amul already possessed the vast data pool, needing only a mechanism to make it actionable at the farmer level.

Experts in the dairy-tech space acknowledge its significance. Sreeshankar Nair, Founder of Brainwired, a dairy-tech startup, identified three key challenges Amul AI can address: farmer awareness, access to quality veterinary guidance, and connectivity to grazing and feed resources. Nair envisions a "White Revolution 2.0" if AI can integrate local dialects of Indian languages, given the linguistic diversity among farmers. Saswata Narayan Biswas, Director of the Institute of Rural Management, Anand (IRMA), views Amul AI as an "instrument of inclusive rural transformation," embedded within a cooperative framework. He notes that the specific capabilities Amul AI brings—such as predictive disease detection, oestrus tracking, optimized feed formulation, and localized weather risk advisories—are advancements Amul has been developing for years, now accelerated and democratized by AI.

The launch has garnered high-level government support, with Gujarat Chief Minister Bhupendra Patel launching the platform and confirming its showcase at the AI Impact Summit 2026. Amul has partnered with MeitY and the EkStep Foundation in building the AI layer. Notably, even farmers not affiliated with Amul can access general dairying and animal husbandry information through the app. At its current scale, Amul AI already covers nearly 3 crore (30 million) cattle, surpassing most national veterinary databases globally.

However, the harder question for any population-scale AI deployment remains: whether the tool will truly serve those who need it most. Farmers already comfortable with smartphones and Amul’s digital system may not be the ones with the greatest information deficit. Key metrics for success will include the rollout of Bhashini-enabled dialect support, the adoption rate among feature-phone users relying on voice calls, and whether AI-driven advisories translate into measurable yield improvements. Amul has built an AI system grounded in half a century of real cooperative transactions, animals, and farmers, providing a credible foundation for large-scale AI dairy farming. Its ultimate fulfillment will hinge on execution and Sarlaben’s ability to reach the 'last few miles'—the most challenging segments to connect.