3 ways artificial intelligence can benefit agribusiness

Artificial intelligence is a tool that the poultry industry can use to leverage data and improve operations.

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Leowolfert | Dreamstime.com;
Leowolfert | Dreamstime.com;

Artificial intelligence is a tool that the poultry industry can use to leverage data and improve operations. 

“Artificial intelligence has the ability to learn from data and experiences instead of being explicitly programmed to perform a task,” Barney Debnam, WW Agribusiness Director, Microsoft, explained during AI in Agribusiness: Been There, Herd That, the keynote session at the Meat Industry Summit 2021.

“Fundamentally, artificial intelligence is the capability for a machine to perceive, learn, reason and, most importantly, extend the abilities of human beings and organizations.”

Artificial intelligence encompasses a range of digital technologies, including expert systems, data mining, predictive analytics, machine learning, deep learning, neural networks, genetic algorithms and more.

During the session, Debnam highlighted three benefits of artificial intelligence to agribusiness.

Connect and gather data

Poultry operations generate a lot of data. Sensors, audio monitoring and other emerging digital technologies can help automate the data management and collection process, freeing up human labor to perform other tasks. 

“The first step is simply connectivity around data assets and human beings. How can I detect and gather data both at the edge and throughout the supply chain?” said Debnam.

Becoming predictive

Artificial intelligence can also benefit operations by identifying patterns and providing contextual advice for possible areas of improvement in poultry operations.

“The second step in the journey is all about becoming predictive. How can I use those data sets and drive some predictability in order to understand the causes and effect and predict what might happen?” he added.

All around cognitive

“The final step in this journey is all around cognitive. It’s driving feedback loops to create better outcomes,” Debnam concluded.

At this stage, artificial intelligence builds on previous data to identify areas of improvement, act on them and assess the results with the next loop, learning from the mistakes of the previous loop each time.

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