Artificial Intelligence Expands Food Technology Options

The European and North American food and beverage markets will see significant growth in use of artificial intelligence (AI) during the next five years.

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By Elizabeth Brewster

The European and North American food and beverage markets will see significant growth in use of artificial intelligence (AI) during the next five years, predicted Heath Branum, Infor, speaking at the IFTNEXT session 705 at IFT20.

Asia-Pacific countries currently have the highest growth rates for AI use in food and beverage, so Europe and North America have much to gain by leveraging AI, he says. In fact, 72% of all business leaders say they believe AI is going to be fundamental and call it a “business advantage,” reports PwC.

computer workFood technologists have numerous opportunities for optimization using machine learning, where algorithms are given data and asked to process it without predetermined rules. Market analysis, recipe building, predictive yields, and safety regulations are just a few of the areas where machine learning can help streamline and expand the work of food technologists. AI can push beyond the limits of common digital tools such as Excel and dashboards to understand patterns and make predictions.

Food technologists exploring how they can best implement AI and machine learning solutions should start by determining how they want to use the processes. In new product development, for example, machine learning solutions could match up consumer test data with current company project trends to find new areas to explore, suggests Eric Krums, Infor. For supply chain, AI could expand opportunities to leverage information about seasonal ingredient availability.

“I think a lot of all that is better predicted from machine learning and AI than it is from the typical resources that we see in place today,” says Branum.

In one Infor case study, Flint Hills Resources—a refining and manufacturing company in Wichita, Kan.—wanted to gain a better understanding of asset maintenance patterns and predict when the next work orders would be necessary. The company also sought to predict overall demand for parts to reduce inventory and improve maintenance work processes. Through its implementation of AI processes, Flint Hills achieved a $10 million potential savings in inventory reduction and a $50 million potential contribution per year in transforming its maintenance business.


Learn more about solutions that AI can provide by viewing this complete session in the SHIFT20 on-demand library.

Registration for SHIFT20 provides access to the on-demand library of sessions for a full year.

SHIFT20 IFTNEXT content is supported by the generous sponsorship of Ingredion.

Kelly Hensel

Senior Digital Editor, IFT

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