 Live from Orlando, Florida, it's theCUBE. Covering Enterprise Connect 2019, brought to you by 5ix9ine. Hello from Orlando, I'm Lisa Martin with Stu Miniman. We are in the 5ix9ine booth at Enterprise Connect 2019. We're excited to welcome back to theCUBE one of our alumni, Jonathan Rosenberg, the CTO and head of AI at 5ix9ine. Jonathan, thanks so much for joining Stu and me on the program on day one of this big event. My absolute pleasure, I'm super excited to be here and super excited to talk about my favorite topic, so love to be here. So this event has been around for a long time, 28, 29 years, evolving from PBX to VoiceCon Enterprise Connect. You've been to this event about the last 10 years or so. At least, yeah. Give us your perspective, and I know you're new at 5ix9ine, but your perspective on the evolution of, not just the contact center, but customer experience and really this changing landscape of how enterprises people want to communicate with each other. Yeah. Well, I mean, it's been funny to sort of watch this through this technology evolution that manifests at the show and in the market. You know, for a long time it was about hardware, right, big, hulky iron, and we used to have the hardware petting zoos, we call it. You'd have racks of equipment, you could go, ooh, look, there's blinky lights and cables, you know, and then it moved to software and we saw that here and now we're deep into the software as a service, SaaS, cloud-based delivery models and actually in a bunch of ways we're coming to the tail end of that into this AI era and that's what's all the hotness and you see tons of that, almost everyone's put some kind of AI logo or branding on their stuff and there is some real meat to it, but that's sort of this interesting evolution and it's in its infancy in the contact center and that's what's sort of exciting about it. Yeah, so let's dig into that a little bit because as Lisa mentioned, you've worked for a couple of the other companies that have big booths here at the show, we've talked about intelligence back in the call center days, but tell us what's different about the AI, data at the center of everything is something that we definitely believe in and something that we hear all over the industry in the cloud shows and AI and everything. Why is this so exciting? What really brought you to 5.9 and you've got a storied career, so why here, why now? Because the technology's finally ready. I mean, technology's like speech recognition and the industry has been working on that for decades and it was only in the last five years or so with the sort of creation of practical deep learning that the tech finally got good enough and that was because of new algorithms, new data, massive data sets, great hardware, that all made it possible and so that sort of opened up the avenues and that's why we're seeing products like Alexa and Siri take off is the tech has finally gotten good enough. But what hasn't happened yet is it hasn't shown up in the workplace and that's sort of what's really exciting to me is to take these technologies that have become so pervasive in the consume world and use them to really reimagine how a lot of these enterprise products work and that's why I came to 5.9. Came to 5.9 to do that, to do that for 5.9, to do that for the industry. So you had a session this morning, five surprising reasons why a business should move their contact center to the cloud and we know cost is not the number one. Talk to us about some of those key imperatives that an enterprise in any industry really needs to be able to take advantage of by moving to cloud. So a cost was a unsurprising reason so what I did in my session was, I said all right, five unsurprising, here's 10, here's 10 obvious reasons so I went through those and cost is one of them. But I know what's surprising, there's a couple, the big one story really is that if you go to a true SaaS player they have lots of customers and they can actually aggregate data, software, capabilities across those customers and do things that are impossible on premise. So the two of them, for example, were better reliability. Often people are like what, you know, I want to go to the cloud, I'm worried about reliability. Well if you dig into it, you can see that once the technology has matured the reliability can be much better than it is on premise because of the complexity that you can build. Same with security, often viewed as, wait it's more secure on premise, actually, if you go look at what you can do in the cloud you can spend a lot more money on security and amortize that cost over multiple customers and then of course there's AI and that's about getting access to training data but not just training data from one company but using it across multiple companies to make the AI work better for everybody. So those are three of the big ones. Yeah, so when you talk about that kind of learning how do you make sure that there's proper firewalls? Is five nine going to be able to say okay we can take care of everything but wait, I don't know, my competitors on this, I don't want them getting advantage based on what my companies have. How do you balance, there's security issues, there's personal information issues and there's competitive dynamics which is a talking point in the cloud these days. Absolutely, I mean so that's a paramount consideration to the design of this whole thing. So it starts with a basic level of like opt in, like we're just, we can't do this and we can't use your data to train a model that's shared unless you want it. And generally it's a give and get. Like oh, if you want access to the shared model then you provide training data for it. If you don't, you can use a custom one but it won't be as accurate but then you don't share your data, it's your choice. So give the customer the option and give them something in return for their data. And of course there's other parts of it like, well almost all the time people aren't actually like looking at your data, it's used to train these models ideally without human in the loop having to do that. And so there's other, there's privacy considerations baked in that it's, that makes it feel, that gives the customer comfort that they're able to do this. Well that trust is critical, right? We talk about it Stu and I do and theCUBE at every show. But that's really essential because as we know as consumers we're more and more and more empowered these days whether we're transacting something through chat or video or Alexa or we're checking on the status of a mortgage or something we have so much information we also are very demanding. I want to have this conversation with a business regardless of the channel and I want them to know what my issue is so that it can be addressed and resolved quickly. But I also want to make sure that what you're doing is not an issue of privacy that we've all faced recently that it's done in a way where this business can actually foster a trusted relationship with me as the customer. Yeah, so the trust goes on many levels. One of which, the most important to us is our customers have to trust us. And the only thing that gives trust is time. You have to be invested for a long time and so we've really focused on building this longtime customer trust with our reliability, with our high touch with our customers and that's really just what gives us permission to even start to do these things. The other thing too to touch on what you said is that end users contact the contact center. That's one of the areas where actually there's already a user expectation that my call is being recorded that what I say can be used for training purposes. So one of the reasons I got into contact center was that the privacy issues are much more readily addressed in the contact center space than other areas where you might be interested to apply this type of technology. I mean, we're talking about having AIs that are listening in on calls and analyzing what you say. If I were to do that for a regular phone call between me and my friend, like people would be totally spooked. Like there's no expectation that that happens. There is an expectation on a contact center. So that's the great place to build and grow these technologies. I love that because those of us that have personal assistants at home, there's almost an expectation that they're listening in a little bit. Everybody's had the, oh wait, I was talking about that with someone, not even on the phone and all of a sudden I'm getting ads for that? That's not right. So question I have for you, you hired your first data scientist in the group and one of the things we look at is we now have this great access to data. One of the biggest challenges is okay, I can get the answers if I know the right questions to ask, what are some of the early areas that you're poking at and the early use cases that you can share as to where we see some. So one of the first things we're looking at is what I'm calling cross customer analytics. So analytics is old news, everyone's had that for a while, but what the cloud does is it gives a provider like us data cross multiple customers. Now what we can't do is share one customer's data as with another. That's a total, it's not what I'm talking about. But aggregates are interesting. So for example, it'd be interesting to know, oh, this is my first call resolution rate. How does that compare to similarly sized contact centers in my geography, right? And that's something where we can produce an aggregate that has total anonymization. So no privacy issues. And it gives a customer this piece of insight that they have never ever had before, never. And the only way you can do it with enough privacy is to have enough data to produce a useful aggregate and therefore it can only be done at the larger cloud contact centers and thus 5'9". As one of the market leaders, we are having an update to produce this kind of information. So this was an immediate, frankly fairly low hanging piece of fruit we've started to dive into. No product announcements. It's just looking at data to see what comes out and see if there's interesting meat there. But it's a kind of insight that I'm really excited about. No, I love that because people are always like, oh, I need to measure it, but sometimes numbers alone don't tell me anything. You got to put that into context for me. What are my peers? What are my industry? What other stuff do I have there? Otherwise, numbers are just numbers. Numbers are just numbers. You don't really know how you're doing. You're like a little island. Like, you know, your contact center is doing, but is that good? You have no idea. And we'll be able to unlock that over time. So very excited about that. Right, sorry, Stu. You guys have about five billion recorded customer conversations. So I can think of the massive amount of competitive advantage that's in there, but you also brought up something that I hadn't considered before and that is whether I'm interacting with the business because I have an issue to resolve with my internet or something. And you're right. We do have this expectation that the call is going to be recorded, but I never think about it as, this is actually something that's going to help me down the line or the 50 other people that aren't calling in. So I thought your comment on privacy being kind of more advanced in the context center was poignant, was very interesting and not something that I was aware. Yeah, it has to be, right? Yeah, exactly. There's an expectation that this is what this conversation is about. And there's lots of tools in place for dealing with today already with credit card numbers and phone numbers, which do get communicated between a user and the contact center agent. There's lots of tech and precedent about how to redact and extract. And again, all in the contact center, nowhere else really does that technology exist. So Jonathan, take us inside the life of the agent. So we know when we went from call center to contact center, it really broadened the role a little bit. When I've got AI in there, is there new skill sets that we need to have? We always talk about if you're doing the same thing you were doing five years ago, chances are you might need to be looking for a new job because they do so fast. So in the contact center, what is the life of the agent likely to go through over the next couple of years? So this is an interesting debate and dilemma in the industry and there's sort of two thought camps in this. One thought camp is the role of AI is to replace the agent. And this frankly is fairly traditional thinking. We use terms like deflection, right? Like we want to deflect the call from an agent. It means we don't want you to connect to a human being or containment, right? How successful were we at keeping the call in the IVR and the customer never got to an agent? Like these are industry terms and people view AI as like helping those things. There's a different camp of which you can tell I'm sort of in, which is like no, no, no, that's sort of the traditional way of thinking about it. And of course we're going to have voice bots and IVRs, but really the question is, how do we deliver the best customer experience possible? That should actually be the guidepost. And what's funny is in this industry, we know what the best customer experience is. It's that you pick up the phone, you call the contact center, you didn't wait one second, you went right to an agent, they were an expert, they knew exactly what to do, they fixed their problem in 20 seconds and you were done. That's the best experience. The problem is, is no one can afford to deliver that experience today. Well, that's where technology can help. And for me, the central question is, how do we use AI to label us to make it cost effective to deliver that experience all the time? And that does have an impact on the agents and it's going to be through assistance technologies that allow the agents to be guided in their interactions and allowing them to be experts quicker and to learn from the best experts in the contact center and change the way they think about training and access to data knowledge. It's going to be a pretty profound change, but it never takes the human out of the loop. People, when you pick up the phone to call that contact center, it's because you actually want to talk to a person and that human touch, that empathy, that someone just to vent out a little bit, that matters and we are nowhere, anywhere near having an AI provide that, if ever. So that's what's going to change. Humans and machines, well, Jonathan, thank you so much for stopping by theCUBE and chatting with Stu and me about what's happening at 5.9 Contact Center as a Service and the tremendous advantage that data can bring to organizations. My pleasure. Thank you guys. If you want to thank you for watching theCUBE, I'm Lisa Martin with Stu Miniman on a program today, live from Orlando at Enterprise Connect 2019. Stu and I will be right back after a short break.