Dairy data and AI: What lessons have we learned?

When Dairy Data Warehouse (DDW) started, the idea was to use the dairy data that’s available on farms (with farmer approval, the data is always owned by the farmer), through advisors and consultants, to improve efficiency, profitability, and sustainability.

At the time, most farms and their industry partners were collecting data in isolation, for example, milk recording organisations, feeding and health records, but none of it truly connected. The company saw an opportunity to clean the data and bring it all together in a single consistent data set.

Since then, the industry’s understanding of data has moved on and along with this, the business has evolved from collection and organising data, to helping farmers make smarter decisions through analytics and artificial intelligence.

Now, data analytics are no longer optional – they’re essential, but DDW says its goal is the same; to use data to help farmers produce better milk, more sustainably.

What does dairy data show?

DDW has spent years connecting, collecting and learning from one of the largest global dairy datasets in the world.

With data from over 28 million cows across 47 countries, the company says its experience shows that the real power of data lies not just in the numbers, but in how they’re transformed into actionable insights. 

One of the biggest challenges in dairy data is fragmentation. Farms often operate multiple siloed systems for milking, breeding, feeding, and health management, and these systems don’t “speak” to each other.

Likewise stakeholders such as genetics firms, nutrition providers, sensor companies, and farm consultants often work in isolation from one another; but they all depend on high quality data.

Precision dairy farming thrives when data is securely shared across stakeholders, enabling collaboration and accelerating innovation across the industry. DDW says one of its clearest learnings is that sustainability and profitability are not independent from each other.

Data exposes where operational efficiency and environmental performance intersect, for example, by fine-tuning feed conversion, improving cow longevity, and minimising waste.

These changes not only reduce carbon emissions but often lead to long-term cost savings and farm resilience. 

DDW has learned how to harmonise these disparate data sources into a single, consistent format. The key lesson: data only becomes powerful when it’s comparable and of high quality.

Consistency is the foundation of trust, and without it, even the most advanced AI models can mislead rather than guide. 

Using AI for predictive dairy farm management  

Historically, farm management has been reactive: addressing issues after they arise, resulting in loss of milk production and not allowing a cow to reach her full genetic potential, DDW explains.

Using big data in dairy, however, allows for proactive interventions. For instance, by analysing millions of historical lactations, DDW’s Predicta tools can forecast disease before clinical signs occur, allowing early treatment and reduced incidence.

Big data and artificial intelligence also help with breeding programmes, guiding farmers and consultants on which cows to cull and which to breed, ensuring the maximum milk yield.

This shift from reaction to foresight helps farmers and consultants prevent losses, boost animal welfare, and optimise herd performance. 

The future for dairy as AI evolves

AI is continuing to evolve and DDW believes that the greatest opportunities for dairy lie in transforming how decisions are made, moving from being reactive to being predictive and prescriptive.

The company sees significant potential in predictive health management, improving animal welfare and reducing treatment costs.

Similarly, precision feeding and nutrition optimisation will allow farmers to tailor diets dynamically, cutting waste and lowering their environmental footprint while maintaining productivity.

Sustainability achieved through AI is an exciting topic; it makes it easier to measure and improve key metrics like carbon footprint and nutrient use efficiency.

DDW is powering the Milk Sustainability Center, a ‘digital ecosystem’ for dairy farmers, where it collects data from both field and barn to help farmers monitor their sustainability. 

These initiatives will be crucial for meeting both regulatory requirements and consumer expectations around transparency and sustainability.

For more information, visit the company website.

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