>> From the SiliconANGLE Media Office in Boston, Massachusets, it's theCUBE! (techno music) Now, here's your host, Stu Miniman. >> Hi. I'm Stu Miniman and this is a Cube Conversation from our Boston area studio. Welcome back to the program. Bobby Patrick, who is the Chief Marketing Officer of UiPath. Bobby, good to see you. >> Great to be here Stu. >> Alright. Bobby, we're going to tackle head-on an interesting discussion that's been going on in the industry. Of course, Artificial Intelligence is this wave that is impacting a lot when you look at earnings reports, everyone's talking about it. Most companies are understanding how they're doing it. It is not a new term. I go back reading my history of technology, Ada Lovelace, 150 years ago when she was helping to define what a computer was. She made the Lovelace objective, I believe they said - >> Right. >> Which was later quoted by Turing and the like is that if we can describe it in code, it's probably not Artificial Intelligence cause their not building new things - >> Right. >> And being able to change on there, so there's hype around AI itself, but UiPath is one of the leaders in Robotic Process Automation and how that fits in with AI and Machine Learning, all of these other terms it can get a bit of an acronym soup and we all can't agree on what the terms are. So, let's start with some of the basics Bobby. Please give us RPA and AI and we'll get into it from there. >> Well, Robotic Process Automation, according to the analysts, like Forester are part of the overall AI broader kind of massive, massive market. AI itself has many different, different, routes. Deep learning right, and machine learning, natural language processing, right and so on. I think AI is a term that covers many different grounds. And RPA, AI applies two ways. It applies within RPA and that we have a technology called Computer Vision. It's how a robot looks at a screen like how a human does, which is very, very difficult actually. You look at a citrix terminal session, or a VDI session, different than an Excel sheet, different than as SASAB, and most processes across all of those, so a robot has to be able to look at all of, all of those screen elements, and understand them right. AI within Computer Vision around understanding documents, looking at unstructured data, looking at handwriting. Conversational understanding. Looking at text in an email determining context, helping with chatbots. But a number of those components, doesn't mean we have to build that all ourselves. What RPA does is we bring it all together. We make it easy to automate and build and create the data flow of a process. Then you can apply AI to that, right. So, I think, two years ago when I first joined UiPath, putting RPA and AI in the same sentence people laughed. Year ago we said, ya know what, RPA is really the path to AI in business operations. Now, ya know we say that we're the most highly valued AI company in the world and no one has ever disagreed. >> Yeah, so it's good to lay out some of the adopting cause one of the things to look at and say if I looked at this product two or three years ago, it's not the product that it is today. We know how fast software - >> Right. Is making changes along the line. Second thing, automation itself is something we've been talking about my entire career. >> Right. When I look at things we were doing 5, 10, 15 years ago, and calling automation, we kind of laugh at it. Because today, automation absolutely is making a lot of changes. RPA is taking that automation in a very strategic direction for many companies there. It's the conversation we had last year at your conference was, RPA is the gateway drug if you will. >> Right. >> Of that environment because automation has scared a lot of people. Am I just doing scripts, what do I control, what do I set? Maybe just give us that first grounding of where that automation path is, has come and is going. >> So, there's different kinds of automation right as you said. We've had automation for decades, primarily in IT. Automation was primarily around API to API integration. And that's really hard, right. It requires developers, engineers, it requires them to keep it current. It's expensive and takes a longer time. Along comes the technology, RPA and UiPath, right were you can automate fairly quickly. There's built in recorders and you can do it with a drag and drop, like a flow chart. You can automate a process, and that, that automation is immediately beneficial. Meaning that outcome, is immediate. And, the cost to doing that is small in comparison. And I think, maybe it's the longtail of automation in some ways. It's all of these things that we do around a SAP process. The reality is if you have SAP, or you have Oracle, or you have Workday, the human processes around that involve still a Spreadsheet. It involves PDF documents. A great, one of my favorite examples right now on YouTube with Microsoft is Chevron. Chevron has hundreds of thousands of PDF's that is generated from every oil rig every day. It has all kinds of data in different formats. Tables, different structured and semi-structured data. They would actually extract that data, manually. To be able to process that and analyze that, right. Working with Microsoft AI and UiPath RPA they're able to automate that entire massive process. And now they're on stage talking about it, Microsoft and UiPath events right. And, they call that AI. That's applying AI to a massive problem for them. They need the robot to be completely accurate though. You don't to worry that the data that is being extracted from the PDF's is inaccurate, right. So, Machine Learning goes into that. There's exception management that's a part of that process as well. They call it AI. >> Yeah, some of this is just, people in the industry, the industry watchers is, we get very particular on different terminology. Let's not conflate Artificial Intelligence, or Augmented Intelligence with Machine Learning, because their different environments. I've heard Forester talk about, right, it's a spectrum though, there's an umbrella for some of these. So, we like to get not too pedantic on individual terms itself. >> Right. >> Um - >> Let me give you more examples. I think the term robotic and RPA, yes, it's true that the vast majority of the last couple of years with RPA have been very rules based, right. Because most processes today like in a call center, there's a rule. Do this and this, then this and this. And so, you're automating that same rules based structure. But once that data's flowing through, you can actually then look at the history of that data and then turn a rules based automation into an experience based automation. And how do you do that? You apply Machine Learning algorithms. You apply Data Robot, LMAI, IBM Watson to it, right. But, it's still the RPA platform that is driving that automation, it's just no longer rules based it's experience based. A great example at UiPath Together Dubai recently, was Dubai customs. They had a process where when you declared something, let's say you box of chocolate, they had to open up a binder and find a classification code for that box of chocolate. Well, they use our RPA product and they make a call out to IBM Watson as a part of the automation, and they just write in, pink box of candy filled chocolate. And it takes its Deep Learning, it comes back with a classification code, all part of an automated process. What happens? Dubai customs lines go from being a two hours to a few minutes, right. It's a combination of our RPA capability and our automation board capability and the ability to bring in IBM Watson. Dubai customs says they applied AI now and solved a big problem. >> One of the things I was reading through the recent Gartner Magic Quadrant on RPA, and they had two classifications. One was, kind of the automation does it all, and the other was the people and machines. Things like chatbox, some of the examples you've been giving there seem to be that combination. Where do those two fit together or are those distinctions that you make? >> Yeah, I mean Gartner's interesting. Gartner's a very IT-centric analyst firm, right and IT often in my view are often very conventional thinkers and not the fastest to adopt breakthrough technologies. They weren't the fastest to adopt Cloud, they weren't the fastest to adopt on-demand CRM, and they weren't the fastest to jump onto RPA because they believe, why can't we use API for everything. And the Gartner analysts is kind of, in the beginning of the process of the Magic Quadrant, they spent a lot of time with us and they were trying hard to say that was, you should solve everything with an API. That's just not reality, right? It's not feasible, and it's not affordable, right? But, RPA is just not the automation of a task or process, it's then applying a whole other set of other technologies. We have 700 partners today in our ecosystem. Natural Language processing partners, right. Machine learning partners. Chatbox partners, you mentioned. So we want to be, we want to make it very easy. In a drag and drop way. To be able to apply these great technologies to an automation to solve some big problem. What's fun to me right now is there's a lot of great startups. They come out of say insurance, or they come out of financial services and they've got a great algorithm and they know the business really well. And they probably have one or two amazing customers, and they're stuck. We, for them, this came from a partner of ours, you're becoming, you UiPath, you're becoming our best route to market because you have the data. You have the work flow. Our job I think in some ways, is to make it easy to bring these technologies together to apply them to an automation to make that through a democratized way where a non-engineer can do this, and I think that's what's happening. >> Yeah, those integrations between environments can be very powerful something we see. Every shop has lots of applications, has lots of technical data and they're not just sweeping the floor of everything they have. What are some of the limits of AI and RPA today, what do you see things going? >> I think, Deep Learning we see very little of that. It's probably applied to some kind of science project and things within companies. I think for the vast majority of our customers, they use machine learning within RPA for Computer Vision by default. But, ya know they're still not really at a stage of mass adoption of what algorithms do I want to apply to a process. I think we're trying to make it easier for you to be able to drag and drop AI we call it, to make it easier to apply. But, I think we're in very early days. And as you mentioned, there's market confusion on it. I know one thing from our 90 plus customers that are in our advisory boards. I know from them they say their companies struggles with finding an ROI in AI, and, you know, I think we're helping there cause we're applying to real operations. They say the same thing about Blockchain. I don't know Stu. Do you know of a single example of a Blockchain ROI, great example? >> Yeah, it reminds me, Big Data was one of those, over half of the people failed to get the ROI they want. It's one of those promises of certain technology - >> Right. >> That high-level, you know let's poo-poo Bobby things that actually have tangible results - >> Yeah. >> And get things done. But you weren't following the strict guidelines of the API economy. >> Right, well true, exactly right. What I find amazing is, I mentioned in another one of our talks conversations that 23,000 have come to UiPath events this year. To our own events, not trade events and other shows, that's different. They want to get on stage and talk. They're delighted about this. And their talking about, generally speaking, RPA's helping them go digital. But they're all saying their ambition is to apply AI to make those processes smarter. To learn from - to go from rules based to experience based. I think what's beautiful about UiPath, is that we're a platform that you can get there overtime. You can apply - you can predict perhaps the algorithm 's you're going to want to use in two or three years. We're not going to force you, you can apply any algorithm you want to an automation work going through. I think that flexibility is actually for customers, they find it very comforting. >> It's one of those things I say, most companies have a cloud strategy. That needs to be written in, not etched in stone. You need to revisit it every quarter. Same thing with what happening AI and in your space things are changing so fast and they need to be agile. >> That's right. >> They need to be able to make changes. In October, you're going to have a lot of those customers up on stage talking. Where will this AI discussion fit into UiPath forward in Las Vegas. We talk a lot about our AI fabric, framework it's around document understanding, getting heavy robots getting smarter and smarter, what they see on the screen, what they see on a document, what they see with handwriting, and improving the accuracy of visual understanding. Looking at the, face recognition and other types of images and being able to understand the images. Conversational understanding. The tone of an email. Is this person really upset? How upset? Or, a conversational chatbot. Really evolving from mimicking humans with RPA to augmenting humans and I think that story, both in the innovations, the customer examples on stage, I think you're going to see the sophistication of automation's that are being used through UiPath grow exponentially. >> Okay, so I want to give you the final word on this. And I don't want to talk to the people that might poo-poo or argue RPA and AI and ML and all these things. Bring us inside your customers. What...where, how does that conversation start? Are they coming it from AI, ML, RPA or is there, ya know a business discussion that usually catalyzes this engagement? >> Our customer's are starting with digital. They're trying to go digital. They know they need digital transformation, it's been very, very hard. There's a real outcome that comes quickly from taking a mundane task that is expensive, and automating that. The outcomes are quick, often projects that involve our partners like Accenture and others. The payback period on the entire project with RPA can be 6 months, it's self-funding. What other technologies doing B2B is self-funding in one year? That's part of the incredible adoption birth. But, every single customer doesn't stop there. They say okay, I also want to know that this automation is, I want to know that I can go apply AI to this. It's in every conversation. So there's two big booms with UiPath and our RPA. The first is when you go digital, there's some great outcome. There's productivity gain, it's immediate, right. I guess I said the payback period is quick. The second big one is when you go and turn it from a rules based to an experience based process, or you apply AI to it, there's another set of business benefits down the road. As more algorithms come out and things, you keep applying to it. This is sort of the gift that keeps on giving. I think if we didn't have that connection to Machine Learning or AI, I think the enthusiasm level of the majority of our customers would not be anywhere near what it is today. >> Alright, well Bobby really appreciate digging into the customerality, RPA, AI all the acronym soup that was going on and we look forward to UiPath Forward at the Bellagio in Las Vegas this October. >> It'll be fun. Alright, I'm Stu Miniman, as always thank you so much for watching theCube.