BlackBerry’s QNX Powers 275 Million Vehicles: Here’s What Comes Next

As artificial intelligence moves beyond chatbots and into the physical world, the software powering our cars, robots, and mission-critical systems is becoming increasingly important. And BlackBerry's QNX division is already powering more than 275 million vehicles with a push for an even bigger role in physical AI on the way. Joining us now is John Wall, president of QNX Software Systems, a division of BlackBerry, to walk us through all of this. Thank you so much for being here, John. My pleasure. Thanks for having me. Of course. So for those people who maybe are not familiar with QNX, what does the business do and how does it really fit into BlackBerry's overall strategy? So QNX builds an operating system and virtualization solution and some middleware components. And the easiest analogy that I can use to help the listeners is think about Windows on your PC or macOS on your laptop. we do that type of software but for mission critical applications so for things that control steering braking something that interacts with people in the physical world if you think about robotics so our product is built to never fail our product is built with the highest safety and security standards and we are what we call a real-time operating system which means we are very deterministic. We react to events in a very consistent way, which is necessary for these mission-critical applications. Yeah, I mean, this kind of operating system, if you will, is so important in all of these applications. And really, as you're talking about, it doesn't have room to fail here. And in thinking about that, in this kind of new application of physical AI, this kind of AI that can really interact with the real world through robots, vehicles, machines, talk to us about QNX and what role it's really playing in making that possible. Yeah, I think, you know, QNX, one of the things that we really focused on in the last few years with our product was making sure that, you know, there are a lot of real time operating systems like QNX in the market. But one of the things that really differentiated us and why we're playing such a significant role in these markets is we really focus on advancing our product for the next generation silicon. For the next generation, silicon is really high performance. It's multi-core. You can start thinking about cloud-level computing at the edge. And so when these companies make these huge investments to buy very powerful chips from NVIDIA or Qualcomm, they want to be able to extract maximum performance from those chips, at the same time maintaining the safety, the security. So what we're doing in these applications is we're providing that foundational layer that allows those companies to focus on applications and bringing value to their products. We want to make sure that car companies are not focused on things in the weeds, that they're focused on features that their customers will pay for or that will differentiate their vehicles. And it's the same thing if we're thinking about robotics, have the really smart robotics people focused on applications, not on this layer. We take care of that. And it's so important as you're talking about now, all of these features, everything that you can do and everything that you can power. But also, as you're mentioning, that safety and that security piece of things. So as these AI systems really become more autonomous, how do you ensure that they can operate in this kind of predictable, safe way in a real world setting? Yeah, and that's the challenge. And there are a lot of standards being developed, you know, that Europeans have a standard called the EU CRA, which is a security standard. We have 21.434 that's been developed for security as well. There's a lot of safety standards. There's a lot of process that goes into this to ensure that the product will behave the way it's supposed to behave, that it fails in a way that is predictable. This is part of the safety aspect of the software. It's very process heavy. it's difficult to do and that's why there are not a lot of companies that do it and we're actually kind of unique in this way that we've been focused on doing this as a company i haven't been there for the whole time but for 40 years and so we've developed a pretty good moat around what we do and again as i mentioned really focusing on on the the performance was one of the highlights in the recent years i should also mention that you know we're working with NVIDIA NVIDIA have their Drive OS and their robot stack, all based on QNX. So we're working with some really important partners and customers to help make the entire system safe. And that safety, as you're talking about, so important, as well as that performance, especially with these different industries that you're serving, right? So you have automotive, robotics, medical devices, rail, aerospace, so many different sectors. Where are you really seeing the biggest growth opportunities right now? Which area are you guys really looking at as you move forward most? So automotive is obviously our big market right now. But I think that where we're seeing the most growth outside of automotive is what I would call industrial automation and robotics. And when I talk about robotics, I know it's cool to see those humanoid robotics dancing and doing Olympics. But really where we're focused today is where the real robots are being deployed and that's in warehouses and factories. And we're talking in maybe a little less sexy robots like skateboards and automated forklifts. But that's where we see the first generation of AI-enabled robotics is helping with warehouses. And then on the industrial automation side, just like we call cars software-defined vehicles, we're starting to see software-defined factories. And what that really means is today when a factory is built, it's built for producing a very specific product. And it's very difficult to change what that, factory can produce without changing a lot of the manufacturing equipment. So what we're starting to see now is a much more software-defined factory that gives the factory a lot more flexibility and controlled a lot more by software as opposed to hardware. And so we see those markets as being very strong growth markets for us. Obviously, rail and medical are big markets for us as well, but they're smaller. Yeah, and it's so interesting to think about that flexibility component that you're talking about there and how that's really become such an important part of all of this as you move forward. And thinking about BlackBerry in general, I mean, it's undergone such a major transformation over the years and QNX now generates nearly half of the company's revenue. So how important is QNX to BlackBerry's future growth and what role does that play in this whole company moving forward? That's an interesting question. I mean, the way we look at BlackBerry, it's two divisions. There's the QNX division and there's secure communication. Like you say, the revenue is is somewhat evenly split uh i think that you know the way we've talked about this QNX is the growth engine for the secure communication it's good solid business generating cash it's profitable uh but we're actually using some of that profitability to continue to feed and grow the QNX business which is the growth business within BlackBerry yeah it's interesting to think about how they kind of fit together here. As you look ahead and AI just becomes even more embedded in our everyday lives, where do you see QNX in the next, you know, if you look five years, 10 years down the line, what do you think we should be watching from in this kind of more macro kind of zoomed out kind of view? Well, I mean, for me personally, who has the vision for the company, I believe if you look five, 10 years out, QNX will be the de facto standard for mission critical physical AI systems in the world. You know, one of the things that we're very focused on is AI in particular. So we are not an AI company. We're not developing AI, use AI, obviously, for lots of things that we do. But what we're really focused on, and we're working with some partners on this, is how do we ensure that AI is safe? How do we ensure that the AI workloads that go into systems and factories and warehouses and cars is going to serve us and is going to serve us in a safe way i think it that is kind of our pedigree is safety and security uh horizontal play we're not going to build stacks we're not going to build robots we're not going to build cars but we are going to really have a very horizontal play across the industry and the beauty of what we're seeing in the market is the requirements for robotics industrial automation medical rail etc they're no different than what we've done in automotive It's not like we need to develop a new product or, you know, put a lot of engineering effort into something. It really allows us to continue to work on evolving the safety and security platform, which now involves AI as well. Yeah, it really does. And that safety and security is on top of everyone's mind as they look forward to the future of AI and where this is all going. So we really appreciate you being here and walking us through all of this. John Wall, president of QNX Software Systems, division of BlackBerry. Thank you so much for your time today. Thank you.