Nicholas Cumins
Management
We are already with AI when it comes to asset operations, as I just explained, we've had capabilities there for a couple of years now, which also made the acquisition of Blyncsy, which is also leveraging AI in order to detect what's going on around the transportation network. We are absolutely excited about the potential of AI when it comes to helping engineers in the design phase. This is very early stage as an industry overall. We are in exploration phase and we previewed what we're working on, which is when relevant for some of the engineering firms, leveraging AI as a copilot when it comes to evaluating different site layout options, leveraging AI in order to automate some production of drawings that is really just a sync of time for them right now. The overall vision we have is AI to empower the engineers, not replace them. And we use our own experience actually as an analogy. Our own engineers are leveraging GitHub Copilot to be much more productive. GitHub copilot as I explained in the prepared remarks is taking over all the mundane tasks so they can really focus on high-value tasks. So, we see exactly the same for infrastructure engineers. And we -- the potential is huge, as I mentioned two weeks ago, in every conversation with infrastructure engineering firm CEOs, AI came up. So the potential is huge for sure. We all see the same. Our approach is going to be leveraging our own engineering applications to train the AI agents not the data of our users, which is different from an approach that other companies may take, right? So, we will train the AI agents with our own engineering applications so that they can learn from entering applications, whether the engineer roles, right. And based on this, we'll be able then to suggest site layouts or components of designs of infrastructure, et cetera, going forward. And what we envision is our users will then leverage their data to fine-tune those models, those AI agents, this copilot will give to them. So, it's a quite distinct approach from what you may see in other industries, actually very adapted to our industry infrastructure and very much resonating. The idea of AI is a copilot, the idea that we training with our own engine applications that we let the users decide when and if they want to use their own data to fine tune. This is what's really resonating. With exploration right now with a number of engineering firms gaining us feedback, the time line for us to deliver those capabilities will depend on that feedback.