When people think of Artificial Intelligence, they often imagine chatbots answering questions. But the most powerful applications of AI may look very different.

Consider “Sarlaben”, the AI-powered dairy assistant launched by Amul in Gujarat. At first glance, it appears to be a simple advisory tool for dairy farmers.

In reality, it represents something much bigger. It is an example of how AI, proprietary data, and domain expertise can come together to solve a real business problem at massive scale. Today, over 36 lakh milk producers across more than 18,500 villages contribute to Gujarat’s dairy ecosystem.

Every day, millions of decisions are made by farmers:

• Is my animal healthy?
• Is milk production dropping?
• Is nutrition adequate?
• Is vaccination due?
• Is breeding being managed correctly?
• Is fodder quality sufficient?

Traditionally, many of these decisions depended on experience, local advice, or access to veterinary support. Now imagine if every farmer could access the collective intelligence built from decades of dairy operations.

That is what makes “Sarlaben” interesting.

The system is built on one of the world’s largest dairy datasets:

• More than 200 crore milk procurement transactions annually, veterinary treatment records covering nearly 3 crore cattle, around 70 lakh artificial inseminations every year, satellite-based fodder data, decades of cooperative farming records. It is an AI-powered decision-support system. For example, milk production data collected daily from an individual animal can become an early warning system. Instead of waiting for a visible problem, farmers can potentially act earlier. This is where AI becomes valuable. Not because it “knows everything.” But because it can detect patterns across millions of observations that no individual farmer could possibly track.

The larger lesson for business leaders is important.

Successful AI is rarely about the model itself. The real advantage comes from combining: Domain Expertise +Proprietary Data +Operational Workflows and
Artificial Intelligence. “Most pharmaceutical companies already possess 10–20 years of prescription data, CRM data, doctor engagement data, sales force activity data and training data. The question is no longer whether AI exists. The question is whether we can convert these data assets into intelligent decision-support systems for managers.”

Business AI Cases is a weekly series from NextPlan Consulting exploring practical applications of Artificial Intelligence and the business lessons leaders can learn from them.