Anheuser-Busch InBev(AB InBev) is using artificial intelligence to drive growth and innovation across all dimensions of its global brewing business.
The brewer of Budweiser, Corona, Stella Artois and more than 500 other beer brands has built a worldwide analytics platform on the Microsoft Azure cloud, enabling the company to draw data driven-insights about everything from optimal barley growing conditions to drivers of successful sales promotions.
Tassilo Festetics, AB InBev’s vice president for global solutions, shared insights about the company’s AI strategy at a recent AI in Businessevent in San Francisco, which Transform edited into an abbreviated Q&A.
How is Anheuser-Busch InBev using AI today?
The question is not going to be where we deploy AI, but where is it not going to be deployed, because we see it in so many different fields.
Can you share an example or two?
Smart Barley, which is one of our platforms, enables us to work with farmers to use artificial intelligence to improve their yields, reduce water usage, reduce fertilizer usage and create a much more sustainable environment. We started there five years ago.
Now we see AI in the customer-facing area with chatbots and voice. Customers are expecting to have the same frictionless interaction with every company that they’re also having in their private life. Conversational bots that allow your customers to interact with your company in that way are a basic machine learning algorithm.
We also use AI in our supply chain and back office operations. We use Azure to simplify tasks that people are performing every day and to make people’s lives much more focused on real added-value activities rather than just on transactional activities.
How did you get started in your AI transformation?
When our company was born the cloud was not there yet. Microsoft was even not there yet. We were born in 1366. So obviously we are not a digital company. We are a company that’s being digitized.
Our company has grown over time, as a large global organization our data landscape was fragmented. For us the first step was really looking at how we basically get data together, how do we harmonize it, how do we platform it. When we looked at the entire data infrastructure we said, ‘OK let’s just not touch it. Let’s hope it doesn’t break.’
We basically rebuilt everything totally as if we were starting a new company today. With advantages in technology and the cloud you can do that. And that saves a lot of time and allows you certainly to be much more agile. But for sure it’s the biggest barrier to get that data right at the beginning.
How did you develop AI expertise within AB InBev?
We were very lucky that our senior management understood very early on that this was something that we should work on. So we were early to invest in new resources to join the company, because obviously we didn’t have them around. But then we also started to develop and improve the capabilities of our own people.
Last year I took my entire team to Berkeley. We spent a week on just machine learning. And it was very fun, because normally if I take my team anywhere, they are very — well, they know a lot of things. So if you put them in a room with professors after one day they will probably be explaining to the professors how life works.
In this course about machine learning you could hear a pin drop after the lesson, because everybody was still processing. And that’s, I think, the important part — that you really continue learning and you continue to build those capabilities inside of your company.
By getting new people in and by developing new skills in your people you start to see different approaches to problem solving. These people will start to find ways to deploy new technologies, new methodologies inside of the company to provide better customer service, better waste management, improved ROI on certain activities. It really starts a different way of thinking.
What advice would you give to companies that are just getting started with AI?
Really start looking at your data early, because data is the fundamental part. There is no AI without data. Then start looking at the areas where you have the best business cases, where can you drive the most value for your company.