AI Series 2.0 #2: Jair Ribeiro, Analytics and Insights Lead at Volvo: Driving Change with AI

0:00Your breakfast probably were delivered by a Volvo truck so far today. there is a big possibility that was. If we have also automation of deliveries, automation of fleets, automation of the last mile deliveries, our impact will be really bigger and bigger and bigger.

0:26Welcome to the second part of the Tech Leaders Podcast AI series, following the incredible conversation with the majestic Maggie Philbin. Professor Carenza Jennings and I are once again thrilled to speak with a true thought leader in the AI space, this time from the automotive industry. Volvo, approaching its 100-year anniversary, is one of the most iconic automotive brands globally. And furthermore, they are at the forefront of the AI and generative AI innovation curve, pushing boundaries and doing remarkable things in this space. Today, we are excited to introduce the analytics and insights leader from Volvo, the brilliant Jair Ribeiro.

1:09Growing up in Brazil, Jair moved to Europe, where he worked at major industry players like Hewlett-Packard, IBM, and now, of course, Volvo. As an expert in both traditional and generative AI models, and with a deep understanding of the ethical dimensions of AI adoption, Jair is exceptionally qualified to dive into these critical topics. Beyond his role at Volvo, Jair is a recognized thought leader in the AI innovation space, frequently speaking at major automotive technology events and also sharing his thoughts and expertise through his popular channel on blogging platform medium.com. In this conversation, we dive into a wide range of topics from ethical AI and the diverse application of generative AI in the automotive industry, jobs displacement, and what most organizations get wrong when implementing AI capability, and so much more.

2:06This one is a real treat. Carenza and I really enjoyed this one. So without further ado, here is Jai Ribeiro.

2:22Jair Ribeiro, thank you so much for coming on to the Tech Leaders podcast. Carenza and I have been so excited about this one. Volvo, a global household name brand, doing some amazing things in the AI space. Highly innovative automotive company that we all know. So we're really excited to talk to you. Thank you for coming on. Thank you. Thank you for the invitation. Really excited for this conversation. There's a lot of things that I hope we can talk together today. Yeah, you've had such an incredible career journey so far. So we're so excited to talk to you. Thank you. Absolutely. So let's start off with a big question then.

2:58What excites you most about the widespread adoption of AI technology, Jaya? Yeah, I would say that this is one thing that we are seeing the last years growing and growing so far, and especially with the adoption of now generative AI. What's really exciting is the democratization. We're going to take AI, a super powerful technology, into the hands of millions and billions of people directly, because some people will use AI directly in their tasks, but some people will benefit from AI embedded, even in a transparent way in our ways. Think about my industry, transportation. if we manage to get the most promised benefits of AI.

3:49We're going to take transportation to billions of people in a new way that it's not been done so far. So I'm really excited about how things are going on the AI perspective. We are in the early stage, to be honest. More will come. But the democratization, it's really important. So democratization with responsibility probably we need to have on this also, because every technology can be used in many ways. We need to be responsible and ethical with AI. So that's if we manage to do that, that would be a great thing. How did you get interested in AI in the first place? Because you're quite a forward thinker.

4:31And in fact, you've got your own blog and you are a thought leader in this space. But what actually took you here in the first place? It's very funny because I was not born a tech guy, just to be honest. I was really humanistic as for background and everything. I also have a master of design and photography. Think about it, something like this. But at the end, when I was growing in my career, I would start to be exposed to the transformations that technology comes. And then I start, well, I want to be part of this. You know, I was studying photography when the digital photography comes. And then I start, oh, wait, there's something going on here.

5:17We are going from the analogical to the digital. And then I start to be exposed to the background of that things. And then I start to build my journey as an employee. and then I say, well, I want to be part of this. I want to lead this thing. I just want to be a consumer because then I can bring my views and we can enable other things for that. And this has happened from the last 20 years until today. I really want to bring forward technology as more into the hands of more people as possible. And is that background in sort of design, so you clearly have a good eye, you know what you're you know the aesthetics and the composition the sorts of things you must have mastered earlier on in your career do you bring that to bear when you're doing your analytics work it's really necessary in an incorporate environment where i am today people are not only interested in on the raw numbers people are not only interested on the hard part of that analytics that say digest numbers everything you need to explain you need to put some storytelling behind of the numbers you need to showcase them in a way that they are not scared by they are not let's say disturbed by the cruel and cold through behind the numbers so having a a real eye for design it's important when you are building also when my team is building ai solutions that for the everyday tasks that my people have, we need to have UX discussions, very important UX discussion, because one thing is to solve the problem with AI.

7:08One other thing is having people using that solution. That's why I love that solution that OpenAI put in our hands so far, because It's a very powerful model, large language model, GPT thing. But if the user experience was not there, nobody will talk. Maybe 10 people will talk about this so far. But what's really changed the game and the user experience? In user experience, it's really, really rely on design, on how people would like to interact with that solution, et cetera. So I'm really happy that I have that background that I can use today in things that technically are not really directly connected to those.

7:57You know, if you are a photographer, maybe it doesn't really look directly connected to your leadership in AI, but it is because AI is multidimensional. AI in companies like us is not one technology. It's not a calculator. It's a multi-dimension. It requires a lot of skills and cross-collaboration. I had a similar path as an aside because I was a television producer for a long time before I moved into data and AI. So that background really, you know, whatever you learned in the past, whatever you did, you carry with you. So what's happened? You can apply this in the things that you are doing today.

8:38So I love the journey, let's say like this. I was going to say the AI sort of capability got implemented into photography equipment quite early, didn't it? I think it was because of the digitalization of cameras, which happened. There's the famous story about, was it Kodak invented the digital camera and then suppressed it because it would ruin their business model, essentially. And then obviously we all know what happened after that. So can I ask you, Jair, about your, I know you spent time at IBM, which was a particularly important part of your career, which I think shaped a lot of your journey.

9:14So can I just ask you very specifically, how did your experience at IBM shape your perspective on AI and cloud technologies? I always say that I'm an IBMer. You know, almost an IBMer, you'll always be an IBMer. I entered in IBM as a pure technician. My role there was really technical. But when you are inside a company like IBM that where learning opportunities and challenges are endless, happened that I discovered artificial intelligence almost by accident. It was not accident because IBM was a top leader of AI with Arc. IBM Watson at that time, so the exposition was natural there. But I made this transition from the technical perspective only to a leadership on AI in IBM.

10:11Before I become a leader in AI, I become a leader in AI in my mindset. And that's what IBM allowed me to be, because that's what I did. I was working in the separate departments, but leading AI projects in other ones. So IBM allowed me to think as an AI leader in that one. And being exposed to the structure environment of AI allowed me also to learn how to apply those things in a corporate environment because that was a great game change for me. Okay, AI, there's AI for consumers, but AI for companies. And what I want to be in the AI for companies because the scale of things and the impact I can do are really, really bigger so far for myself.

11:04So that's why I changed my completely role to go all in in artificial intelligence for companies. Yeah, that's a little bit like the allegory of IBM itself. The IBM story is extraordinary. The fact that it's reinvented itself so many times and it has managed more than many other companies globally to stay relevant and to ride the crest of the wave between software and hardware. And when you are there inside, you learn to reinvent yourself. That was one of the biggest thank you, I say, to IBM for the years I've been there. They allow me to reinvent myself internally to the company. And then I did the rest.

11:50But of course, if someone really helped you, that's you must say thank you forever on that one. I love this, the marketing strapline that they sort of pushed out in the 80s and 90s, which was nobody ever got fired for buying IBM. That was so successful in the B2B world, wasn't it? I saw a recent study. And when IBM comes out with a study, you trust the numbers. And they have predicted that on an annual basis, in America alone, in the United States alone, $3.1 trillion is being lost per year due to poor data quality. and when when IBM says that I mean that's an astonishing number you do believe it and you think the opportunity is there isn't it and data quality it's the critical foundational conversation we need to have with everyone before I talk about AI because data quality in companies like mine and every other enterprise.

12:55It's a challenge. And to reach the value that we want from AI, first, we need to make our homework on data quality everywhere, not only my company. Every large company that I know are struggling on this. And I totally agree that IBM really point the finger to data quality. and when IBM does on this one, we should hear. I'm really happy to share this kind of reports with everyone because we need to make our homework in data. Yeah, that's a really good point, actually. So can I ask you on that one? What's the biggest mistake you see businesses make in terms of their data then, Jair? That's a real complex question because we saw a lot of mistakes on this across the journey.

13:47The fact that I see also some leaders waiting for the perfect data, this can be a risky mistake because you will never have the perfect data across your whole domains or the whole company. But there are domains that are more mature than others. And when it comes to quality, that you should focus with artificial intelligence. So if a certain domain like marketing are more advanced on data collection and curation of everything, their data is fed, it's better start with AI debt, win some fights with that, and then show to the rest of the company, okay, that's the roadmap. But what market did to arrive on this quick win here, they work a lot of data, they enhance their quality, everything else.

14:41So now what's the next domain? Let's start to work on that because there's no perfect data across the company. Because even data that can be absolutely crappy for marketing can be absolutely perfect for HR or for security or something because it's really contextual. well. So I see so many people waiting for the perfect occasion to start with AI and that would take years and years and never can. That's such a great point, not just about waiting for the perfection of the data, but thinking about how can you use the same data sets for different applications and having that level of creativity within enterprise is where you help unlock your savings.

15:29Because of course, your usability, it's very important for save cost saving and speed, etc. So if you build a good data product in a certain areas, push to reutilize this as more as possible across the company, so you don't need to reinvent the wheel, redo everything, etc. So that data domain or data probably is good. Let's spend time and money on getting people using this. Then the AI solutions will be put on top of that data. And then the value will come out from that one. And then you go to the next, next, next, next. Yeah, absolutely. I really wanted to ask you, Jay, quite recently, which was quite well into your career, you decided to go to MIT and further your education.

16:21Can you talk us through why you decided to do that and what you learned from that experience? You know, it was a moment that in my mind and for the mind of many people, data science was the sexiest job in the world. So it's, okay, let's check it out this. And then I can confirm that it's really close to that. So it means that it's important to have the right background when you want to really work with advanced technology. So that was for me the right thing to do in that moment. And I'm really happy about this. I get an extensive background on data science and analysis that helped me today, even when I'm not really hands-on today.

17:10but I understand when my data science talk and everything else about the complex job that we have to do in our everyday activities as a team. So, and of course, building the network, it was very important also. The network with leaders and peers in the area was very important. And so it was a great trampoline to tackle further challenges in the data science areas. As a leader, did you find that having that deep learning gave you a greater sense of confidence to help your teams decide what not to do as well as what to do? Yeah, I would say that, you know, greatest level of confidence are always challenged in my job every day because every day we see, we meet some challenges, some business issues that really challenge my confidence so far.

18:08But it's allowed me also to know what I don't know. That's one of the most important things that I take when I enter to the room to discuss problems and the things that I'm not aware of or I don't know. So I know what I know. I know there are a lot of things that I don't know, and I try to work on the things that I don't know. But if you don't have this awareness, you get in the confusion of, I know everything. That's a very risky challenge. Or I don't know nothing that it's really not a good also position to be. So I really believe on continuous learning. What I learned for years, it's very useful, but it's sometimes not applicable today.

18:52So I need to continue to learn. I never stop. So that thing was a trampoline, but I'm still jumping in many, many other areas. Today, for example, in the last month, I saw myself coding again. I was born as a developer, as a coder. Today, I'm coding. I'm coding more using generative AI. I'm coding more and faster than when I was really get paid to code so far some years ago because the technology has helped me a lot. And can I pick up, because you going back to coding is super exciting, because it also just keeps you feeling that you're kind of really stuck in. And you're also experimenting with the new tools as they emerge.

19:40But back to your point about the democratization of AI and generosive and the power of that. What's your point of view about code and no code and low code models? I think this is super important. I think that even people that don't have all, I put myself in the condition to think, what if people that don't have all the background I have as a code developer working for companies doing this, they can do what I'm doing here? Normally, my answer is yes, they can. I try to play with my daughters. They are starting to build things. But also, sometimes I think, what if a guy in Africa is starting her journey today and have access to this kind of tools that could help him to develop the next application that the world will use so far?

20:34without all the tools that we have would be really hard. But today, if we democratize this kind of AI for all the world, that's really philosophical, but I think we should go there. That's ideas and opportunities will come in many, many, many ways. So that's why I love initiatives like the Khan Academy me that it's trying to really bring the AI in this perspective. I love also initiatives that are happening today to bring code to girls around the world and make them develop their ideas with AI, using AI and develop together with AI. So democratize this. I think it's our responsibility if we are leaders on these areas so far.

21:29Beautifully put. You know, absolutely. No, that's really good.

22:00your processes and ensure robust governance so that AI works effortlessly to drive real results. Curious to learn more? Visit bedigitaluk.com or follow us on social media to discover how AI can transform your business.

22:22Can we talk about your current role then, Jair? You're obviously the analytics leader within Volvo. Would you be able to maybe give us what is the purpose of your role? What is the main objective of your role? Yeah, I was not in the Volvo trucks part of the company when I saw this job. When I saw the job description, I was thinking it was written for me. So I immediately apply for that. Okay, I want that job because this is exactly what I want to do in my career. It's really fascinating how can I have an opportunity to lead a team of innovation with artificial intelligence. It's a team dedicated to experiment, to bring, to catch the ideas across the company, prioritize them that it's really important in a company like us to really choose the best one based on feasibility or business value or whatever.

23:18we have our criteria and then we prioritize them, experiment them, develop them, then make them grow these ideas. And when we see that these are the best ones, we have process to make them go from our hands and go to the other levels of the company. So when I saw this, okay, this is where I want to be because it's a great company, of course, the Volvo Group, and they have resources to make these things happen. And if I can put my enthusiasm and my passion and my energy on that, I'm really sure that we're going to try to do a lot of great things together. And it's happening. I'm really happy about how things are going.

24:07Now, in the meantime, I joined this role two years ago. So in the meantime, it's evolved. Now we are getting more, a bigger scope as a team. We are having a bigger scope as AI and analytics division. And I hope that, and I really think that the best is yet to come. And do you feel, I mean, culturally speaking, the Volvo group, do they have that courage to back innovation? Because when you're coming up with your new ideas and you're doing your pilots, sometimes it can be hard to see exactly what the value realization will be at the early stage. So culturally, do they have that kind of bravery? I would say that, first of all, the Volvo Group, it's really a traditional search environment from the enterprise perspective.

24:59From the risk perspective, we always prioritize safe in everything. safe in the vehicles by safe in even the most simple application that we deploy, safe come first. So this makes the mechanism sometimes that can look complex and sometimes look slow. But when you really look in how people are working together to put things, I'm really excited how the innovative mindset. You can see this outside from the products that we have. If you see the vehicles that we did and the technology is there, you can touch with your hand so you know that it's innovative. I see the everyday way of working that we have and having even the side that we have as a team dedicated for innovation is a good side because that's the best companies in the world has this approach.

26:00Let's nurture, let's feed innovation with our culture. And when I go to talk with people about culture and innovation, the open doors are amazing. So it means that the culture is here. It doesn't mean that it's easy. It doesn't mean that we don't have resistance. because there are also other, in 100 ,000 employees, statistically, you're going to find resistance for any change you're going to do. But the culture, it's really good here from the perspective of leadership. We have great leaders. I always like to say that I have the best managers that I have in my career here in the Volvo Group in Sweden, and also top leaders that inspire me.

26:51So the people that I work are super helpful and managers that really want to see things getting done. And I have, when I look up, I see great leaders inspiring me. Of course, every day we have bad days, good days. I have bad Mondays too. Don't think that I don't have, I have it. But when I need this culture to back up my work, I always find. And then when I find the resistance, I hope to have my smile to help. It helps a lot. And the expertise that I accumulate along the years also help to find resistance and change and manage change. Because AI, it's really connected to change management. I think your enthusiasm and your smile are definitely good weapons, certainly for conflict resolution, Jair, for sure.

27:48I'm sure that's... At least things don't escalate, at least when you smile. Can I ask you, I'm really keen to understand, actually, Volvo, a very traditional manufacturing company, been going for nearly 100 years. How would you describe the culture there? And especially, how does it differ to somewhere like IBM, like an American consultancy firm like IBM? Yeah, we should start from that. What is the different Swedish culture and American culture of way to work? We probably need a new episode of your podcast just to talk about it because it's a long story. But anyway, if you compare both companies, both are performing well.

28:31Both are really giving revenues for shareholders, everything. So going out for how performance, we are performing very well. How we do it, it's completely different. The pressure is different. The way of the life balance, it's completely different from the American and from the Swedish way of work. The way you take decisions, sometimes top down in the American way, in Swedish way, it's more consensus. You have a lot of discussions to make the decisions. Sometimes the decisions take more time, just to be honest, take more time because you need to see here and a lot of perspectives. But normally at the end, when you take a decision, you take the right decision and everybody goes for win on this one here in Sweden.

29:30Of course, in other cultures, not only in America, you have a more strong leader that decides and then sometimes communicates, sometimes not. But the decision is that. Here we have a real consensus. Personally, my background loves this area here, this of decisions, because I like to talk with people. I like to understand their point of view. And then we take a common decision. It takes more time. It takes more effort. Sometimes you don't really decide what you have to do today, but you're going to decide next week because you need to think. But at the end, we make decisions, and hopefully they are the right ones.

30:14I'm really enjoying this way of work in Sweden, to be honest. It's really completely different than all the ones I have, from Brazil, Italy, and Poland. The decision chain, it's completely different. But Sweden is doing very well, thank you. So I think it works somehow. I think also the consensus approach is interesting. across different industries, even in America. I think, for example, Pixar, they have a brains trust approach to the way they create their movies. And that is very, very consensual. So they will have an initial group of people putting together the kind of the writing room, their initial storylines.

31:02And then they have a fantastic culture where everybody is there in order to make the movie as funny as it can possibly be, as relevant as it can possibly be and as wonderful as it can possibly be. And they all come together and they have these conversations around, I don't really buy that that character would say that. So it's sort of, I think there's a little bit of dependent on the sector and the industry as well. Definitely. Especially the creative sector should not be different than that. We need to put people together to think and to discuss. In the IT industry, that chain of command can manifest itself in a more stronger mode.

31:45But I would say that I would prefer to stay on this side of the story. No, I quite agree with you. I think consensus, making time to listen to other people's points of view, you get a greater diversity of thoughts, and ultimately you get a better outcome. Absolutely. Yeah, I think in autocracy, you get the opinions more of one or two people, don't you? the meritocracy or something which is a little bit more democratic, I think you tend to get the opinion of many people. And, you know, yeah, I think it's definitely better for innovation, surely. And that's why I asked that question is because I think that Volvo is obviously a traditional manufacturing company.