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How Unilever is embracing artificial intelligence to revolutionize food development

How Unilever is embracing artificial intelligence to revolutionize food development
How Unilever is embracing artificial intelligence to revolutionize food development


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As artificial intelligence becomes a more important part of doing business in the food and beverage space, few companies have turned to the once-futuristic technology more than Unilever.

The consumer products company uses the technology to revolutionize and expedite the way it makes food products, leading to the launch of several new products such as Knorr Zero Salt Cube, Hellmann’s Vegan Mayonnaise and the Hellmann’s Real Mayo Squeeze Bottle.

Unilever is incorporating the technology across all facets of its business. AI helps the London-based company asses shelf life, texture and taste while predicting how the product will perform on factory lines during production. Unilever also harnesses AI to forecast flavor profiles, understand consumer preferences and boost food portfolio analytics.

Manfred Aben, the head of science and technology for Unilever Nutrition and Ice Cream research and development, recently sat down to discuss AI at the company, how it’s evolved and where it’s going next.

This interview has been edited for brevity and clarity.

FOOD DIVE: How has AI been used by Unilever?

MANFRED ABEN: What you actually see over the last decade or two is that the availability of data has really increased and, of course, also the computing power.

Maybe initially, [AI] was very much used in the marketing side and the consumer understanding side. In the supply chain side, obviously where we can measure a lot of what’s happening operationally and how can we optimize that, while also in R&D, which is my area where it’s really about creating products that consumers prefer, and so how do you make sure that for instance, the products are safe, have a long shelf life? So we use digital modeling and AI to predict shelf life of products so that we then can optimize the shelf life, which is obviously good for the use in consumers’ homes, but also for reduction of food waste, and then overall optimization.

And let’s say to predict flavor profiles, to predict liking of our product so that we probably want to be faster with innovation and really respond to consumer needs fast. You want to be able to understand what consumers want and how you solve their needs optimally rather than doing lots of experiments, either in the marketplace or in the laboratories. So, data modeling and AI helps a lot in shortening that period. So we can actually deliver more innovation to our consumers.

What products have you used AI to help develop?

ABEN: One example is Knorr Zero Salt Cube. Bouillon cubes have been around for a long time. So they’re basically stock cubes. And they’re basically constructed of course of salt, flavor, herbs and spices. But … if you want to make a cube without salt or sodium, or with less sodium, then you have to replace that with something else. And also very importantly, you don’t want to compromise on taste, and also not on how it performs in terms of people crumbling it, how it performs in the soup or in the dish you use it in.

Manfred Aben, an executive at Unilever

Optional Caption

Permission granted by Unilever

 

So what we did was actually when we wanted to design a cube with no sodium, we have to change all the parameters almost like what ingredients could give us that salty flavor? What ingredients could give us that same texture and structure of the cube? We used digital modeling for that a lot, to just go through much data about many ingredients, great ingredient combinations, to then come down to a small set of options that we then of course, developed.

Another example is our Hellman’s Vegan, for instance, where we obviously replace the egg proteins with plant-based proteins. And again, consumers want alternatives that are better for them, better for nutrition, better for the planet because obviously moving to plant-based options is also good for that. But they don’t want to compromise on taste again.

They want to really have that same creamy mayonnaise that they’re used to having. So again, there we used AI models to predict the flavor and consumer liking in various countries where we launch a product so that you can make an optimal design. It saved us a lot of experimentation in the lab and thereby being able to respond quicker to consumer need.

Does Unilever use AI across other facets of its business, like the supply chain, minimizing trial and error or predicting how the product will behave on factory lines? 

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