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Brewing Smarter: How HEINEKEN Is Using AI To Revolutionize Its Global Operations
21 Apr 2026
Chapter 1: What is HEINEKEN's goal for becoming the best connected brewer?
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I'm Malcolm Gladwell.
Chapter 2: How did Surajeet Ghosh's background influence his role in AI at HEINEKEN?
Welcome to season seven of Smart Talks with IBM. This year, we're exploring new stories about how companies are using the latest advancements in AI and quantum computing to create smarter business. For the first episode of the season, I flew to Austin, Texas to join Surajit Ghosh on stage at South by Southwest. Surajit is chief AI officer at Heineken, the world's pioneering beer company.
Founded in 1864, Heineken has deep roots, but it continues to push the boundaries of innovation today. In 2020, the company came up with a goal to become the world's best connected brewer. Surajit plays a key role in leading that transformation.
And I sat down with him in front of a live audience to understand what that journey looks like and what it takes to reinvent a global company from the inside out. And before we get to... the question of what you do in your job. So I'm really interested in people who have jobs that didn't exist for most of their life. And I'm curious how you got there.
Yeah. First of all, thanks for having me here. Actually, it did exist.
Chapter 3: What challenges does HEINEKEN face in implementing AI?
And people sometimes don't realize AI is not new. It's been there for 75 years, since 1950. It just changed over time how the application is happening, right? So one thing to keep up with is as AI became more popular and more embedded in business, how do we upskill ourselves to stay at par with the technology trends? So the preparation for me personally started actually a long time ago.
So when I was in grad school in US, I used to live in US by the way for a long time. You're Indian. I'm an Indian originally, but I used to live in the US. I did my grad school here. And there actually, I started taking courses in neural networks and artificial intelligence back in 2002. And it wasn't popular back then. But I was just curious. What is it? Maybe it's the next big thing.
And I'm so glad I did that.
Chapter 4: How is AI transforming HEINEKEN's supply chain operations?
Because that sort of helped me build that foundation.
What was it? You said you were... You were curious about it. You were curious about it, why? What caught your eye about?
It was very different because the main difference was before that I was an engineer by profession. So I went to engineering college. Everything is rule-based. Everything is based on a formula, a physical equation. AI is something different because it's based on data and statistics. It never gives you a clear answer. It gives you a probability.
And I just thought this is very interesting because if you're trying to solve a problem, you don't know exactly how to solve it. There is no equation.
Chapter 5: What role does data play in HEINEKEN's marketing strategies?
How do you get around that? I think that's where AI comes in. It finds those patterns within data and comes up with some prediction. That intrigued me. So this is what year that you start dabbling? I started dabbling, let's call it dabbling in AI was 2002. So it's almost 24 years ago.
24 years. But what you were playing with in 2002 was an extremely primitive version of what we have now.
I think it was very relevant. Because the way I see it, should I have skipped all the foundations that I learned over the years and just gone to the current state? Maybe, but when I look back, I think that foundation really helped me because back then, and surprisingly, by the way, neural networks, when I talk about that, it's still very valid and relevant within AI.
The entire foundation is neural networks. So I think that foundation really helped. And I still find it very relevant and I apply it day to day.
Chapter 6: How does HEINEKEN ensure employee engagement with AI tools?
Imagine I'm having a conversation with you 20 years ago, and I say, what are you up to? And you say, I'm playing with this thing, neural networks, this early version. Would you have used the term artificial intelligence?
Probably not. I probably would have used something called statistics, which everyone is aware of. Back then, it was more statistical. So you don't have these big algorithms at that point. But then something happened. I don't know if you heard of this company called Kaggle. They used to host these sort of data science competitions and anyone can participate.
And if you do really well, you get a prize. That was a good motivation just to see, okay, I learned something. Let me apply it and see how good I am. I'm getting at it. So I think that was my first entry point where I really got hands-on into AI.
Chapter 7: What metrics does HEINEKEN use to measure AI success?
And that probably stayed with me for a while. I think that was back in 2006. That's when I started getting hands-on. And the funny thing is, when you look at these Kaggle competitions, the use cases they used to give, actual industry applications. So you were really dealing with business problems, applying AI to solve it.
And then you know, wait a minute, a medical company is using it, a manufacturing company is using it, a banking is using it, and this is 2006. So it already started. And then it just, yeah, today it's a different ballgame.
Yeah. Now, so you came to Heineken when? 2020. 2020. Right middle of COVID or right after, yeah. And were you brought in to be the chief AI officer? Was that your title?
Chapter 8: What future innovations does HEINEKEN foresee in AI and business operations?
Correct. The title changed, but yes, I was the global leader at Heineken.
And what made you want to take the job? I was actually working for Amazon at that point. But when I looked at Heineken and I thought, okay, this is a legacy traditional company, right? And AI was not a capability embedded at that point of time. So it's a great opportunity.
If I can start something from scratch, really build it across the entire value chain of Heineken, I mean, that's probably the best job anyone can even ask for. Yes, it's of course a lot of responsibility, that you have to make sure that you really build the right products and right capability. But that also happened. So when I look back, it's quite fulfilling.
But it's also, if I might play devil's advocate for a moment, you're also taking a risk going into an established, how long has Heineken been around? 162 years to be specific, 1864. It's a very different proposition walking into a 160-year-old company and saying, I want to bring the future to the way you operate than it is with a startup.
That is true, but it's also a challenge. It's a good challenge. And also that Heineken is also looking externally. There are companies that are picking up speed and embedding and adopting AI. So should we fall behind? Not really. So we also need to pick it up. So I thought it was a good challenge because the use cases were there, the opportunity I could sense.
the business really was having the appetite, let's do something different. When we apply AI in a corporate setting like this, it's super important to understand how the business actually works. What's the value chain looking like? What are the nuances? And once you get an understanding, it took me some time, by the way, to understand the full business and the complexities.
But once you cross that threshold, you figure out what's feasible, what's not. And then it opens up. Wait a minute, within the value chain, I see 10 areas I can optimize. You say, once you understand the business, describe the business. What is the Heineken puzzle? So, well, puzzle, let's see if it's puzzle after I explain.
It's actually, you start with the procurement where you get the glasses, cans, and all the raw materials. Then it comes to the brewery where the magic happens. That's where the Heineken beer is produced. Then it goes to the distributors. Basically, supply chain takes over. Then it goes to the customers.
And what we refer to as customers are the bars, restaurants, retail stores, mom and pop stores, convenience stores. And that's where actually consumers then come and actually consume the product. So that's actually the value chain. It's actually pretty linear when you think of it, but there are nuances.
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