Richard Poland: This is Rich Poland on for Rishi Jaluria. So I guess, first one is just as we think about some of these new AI capabilities between Copilot, Autopilot and Actions, is there any one that stands out as kind of being maybe a more immediate revenue driver versus a long term? And then, I guess, just a second aspect of that question. Do we have any like sense for the adoption curve of the consumption element? And just kind of how long does it take the customer to start to ramp up some of those volumes and if we have any early proof points just kind of around that?
Barak Eilam : Sure. Let me address the first one, great questions. So in terms of the pipeline, we see test out differently. Customers when they speak to us about AI and they hear about Enlighten, and they want to learn more, they want to see all of it because they see the value of how Copilot augments their existing users. They see the Autopilot allow them to really go into self-service in the right way. And Actions is a completely new paradigm on how managing CX, and it changes dramatically the way they think and see CX. In terms of what we’ve seen, customers are starting with — many are starting with Copilot because they want to take the technology first to existing processes with the agent. It’s also putting it with the agents versus first with the customer.
And this is kind of the safest way to go, but it also allows them to move quickly from Copilot to Autopilot because if something works extremely well with the agent and you can automate it very — relatively easy, you can migrate it into the Autopilot. So that’s what we see more often than not starting with the Copilot moving into Autopilots. That’s about that. And the adoption — as we continue, of course, we’ll update about the specific adoption that we see for the 3 solutions of Enlighten. In terms of the adoption curve and the usage, I think it’s still early days to say. We do see customers that deployed Enlighten and are deploying Enlighten starting to ingest a lot of information to that. There is an understanding of our customers and general understanding that generative AI is good up to a certain point.
And the reason why they go to Enlighten versus using something generic is that eventually an enterprise needs something different. They needed to be precise at 100% with no hallucinations. And for that, you need a lot of data. You needed to be extremely secured. They cannot take something proprietary into the public domain. They need to be connected to all the back-end system, and CXone is the best platform for that when it comes to CX. And of course, they needed to be aligned with the brand. It’s nothing — we don’t want generic answers to their consumers or to the agent. So you add all of that together and the amount of data going through that, I believe that we’ll see a significant expansion. But it’s still, I think, too early to say what is the exact rate of expansion.
Richard Poland: That’s very helpful. And then just one for Beth. You talked a little bit about the accretion from digital and AI. Can you maybe, I guess, step back a little bit and tell us kind of what you’re seeing on the gross margin front from some of those solutions? And how you think about that versus, let’s say, like the core CCaaS business?
