>> Narrator: Live from Las Vegas it's theCUBE. Covering UiPath Forward Americas 2019. Brought to you by UiPath. >> Welcome back everyone to theCUBE's live coverage of UiPath Forward here at the Bellagio in Las Vegas. I'm your host Rebecca Knight along with my co-host Dave Vellante. We are joined by Craig Le Clair, he is the vice president of Forrester and also the author of the book "Invisible Robots in the Quiet of the Night: How AI and Automation will Restructure the Workforce". Thank you so much for coming on theCUBE. >> Craig: Thank you! Thanks for having me. >> And congratulations, it's already made #11 on Amazon's AI and automation bestseller list. >> Wow, it's not quite best seller but OK, that's great, thank you, it's doing well. >> So if anyone calls your book a bestseller you just take 'em on that. >> (Craig) I'll just take it. >> So it is a, it's a bleak story right now, I mean there's a lot, there's so many changes going on in the workforce and there's so much anxiety on the part of workers that they're going to lose their job that all these technologies are going to take away their their livelihood, so how are companies managing this? Are they managing it well, would you say, or is the anxiety misplaced? Give us an overview. >> Yeah, so I don't think companies are really aware of the broader implications of the automation and AI that's developing. They tend to focus on the things that companies focus on. They focus on more efficiency and productivity and so forth, and underlying that is this digital anxiety that we call it, and the fact that a lot of the jobs that we, particularly the middle class have, the working class have, are the targets of the invisible robots, and that's really the point of the invisible robot book is that there's a lot of media attention on the hardware aspects of robotics, in fact the Super Bowl last year had 10 commercials with hardware robots. But if you look at this conference you look at the number of people here. What are these people doing? They're going back to their companies and saying "You know, this UiPath, and there are other providers "in the market, we can build software robotics, "we can build bots to do some of these tasks "that a lot of these humans are doing." And while there is elevation of the human capability in spirit for many of them, there's also a comfort level in employees that do things that they have control over, have incited. And when you extract those you are left with a series of more exciting moments, perhaps, but it's not going to make you more relaxed as an employee. And then you look at the overall job numbers, and our estimates are very conservative compared to some of the other reports, that are 45, 50% of workers over 10 years being displaced. We think it's 16%, but still, when you look at just the US numbers, that's of 160 workers today, 160 million workers, that's a lot of people. >> Rebecca: It is indeed. >> So, displaced and then sort of re-targeted or? >> A percentage, >> Vaporized. >> No, no, well the 16% is the automation, is the net loss of jobs. Now in that, automation's expensive, so there are a tremendous number of new jobs that are created by the work that's been going on here. So we have a formula to calculate that for these 12 different work personas, and the work personas have different relationships to AI and automation, so you would be crossed so many knowledge workers and be very well protected for a long time. >> Rebecca: All right, there we go. >> So you're good, but... for coordinators, people that have clip boards in their hands, for those who work in cubicles, they're going to have a lot of people leaving those cubicles that aren't going to be able to migrate to other personas. And so we have a changed management issue, we need to start driving more education from the workplace through certification, and that's a really critical thing I'll talk about tomorrow, that the refresh of technology with automation is 18 months to 24 months, you can't depend on traditional education to keep up, so we need a different way to look at training and education and for many it's going to be a much better life, but there's going to be many that it will not be. >> What was the time frame for your net 16% loss? >> 10 years. >> 10 years, okay, to me a lower net loss number makes sense, and in fact if you can elongate your timeline it probably shows a net job creation, you can make that argument anyway I don't know if you. >> Craig: It's being made. >> Dave: You don't buy it though? >> I don't, the world economic foundation and others are having huge net new numbers for jobs based on AI. Some of the large integration companies that want to build AI platforms for you are talking about trillions of dollars that would be added value to the world economy, I just don't buy it, and you know the reason I wrote this book was because what's going on here is very quietly preparing to displace a lot of efforts starting with relatively small tasks, it's called task automation but then expanding to more and more work and eventually adding a level of intelligence to the task automation going on here, that's going to take a lot of jobs. And for most of those 20 million cubicle workers, they have high school educations. You know, the bigger problem is this level of anxiety, you know, you go into almost any bookstore and there's a whole section For Dummy books, and it's not, is it because we have this sort of cognitive recession or because there's a, it's because the world's getting faster and more complicated. And unless you have the digital skills to adapt to that, the digital skills gap is growing. And we need to have as much focus that you see here and energy on building automation. We need to have an equal amount of focus on the societal problems. >> Yeah, it really comes down to education, too. I mean if I were able to snap my fingers and transform the educational system, there might be a different outcome but that's very unlikely to happen. Craig, one of the things we talked about last year was you had made the statement that some of these moonshot digital transformations aren't happening for a variety of reasons but our PA is kind of a practical way to achieve automation. >> Still very true. >> Have you seen sort of a greater awareness in your client base that, "You know, hey, maybe we should dial down "some of these moonshots and just try to "pick some clear winners." >> Yeah, we have a number of prediction reports coming out from Forrester and they're all saying basically that. I'm doing reports on what I'm calling the intelligent process automation market and that's really our PA plus AI, but not all aspects of AI. You know, it's AI that you can see in ROI around, you know it's AI that deals with unstructured documents and content and email. It's not the moonshot, more transformative AI that we have been very focused on for a number of years. Now all of that's very very important. You're not going to transform your business by doing task automation even if it's a little more intelligent and handles some decision management, you still need to think about "How do I instantiate "my business algorithmically," with AI that's going to make predictions and move decision management and change the customer experience. All that's still true, as true as it was in 2014/2015, we're just seeing a more realistic pull back in terms of the invested profile. >> Well, and so we've been talking about that all day, it is taking automating processes that have been around for a long time, and you, I think identified this as one of the potential blockers before, if you get old processes that are legacy and I think you, you gave the story of "Hey, I flew out here "on American Airlines in the old SABRE system." How old are those processes, you know? We've, you know the old term "paving the cow path." So the question is, given all the hype around RPA, the valuations, et cetera, what role do you see RPA having in those sort of transformative use cases? >> Well here's the interesting thing that was, I think, somewhat accidental by the, you know what really changed from having simple desktop automation? Well you needed some place to house and essentially manage that automation, so the RPA platforms had to build a central management capability. UiPath calls that the orchestrator, others call it the control tower, but when you think of all the categories of AI none of them have a orchestration capability, so the ability to use events to link in machine intelligence and dispatch digital workers or task automation to coordinate various AI building blocks as we call them and apply it to a use case, that orchestration ability is pretty unique to the RPA platforms. So the sort of secret value of RPA is not in everything that's being talked about here but eventually is going to be as a coordinating mechanism for bringing together machine learning that'll begin in the cloud, conversational intelligence that might be in Google. Having the RPA bots work in conjunction with those. >> But if I recall, I mean that's something that you pointed out last year as well that RPA today struggles with unstructured data that... >> Well it can't do it. >> You're right, we've talked about it NLP versus RPA, RPA, given structured data, I can go after it. >> That's the RPA plus AI bit, though. I mean, you take text analytics layer, and you combine it with RPA bots and now you have the unstructured capability plus the structured capability that RPA does so well. And, with the combination of the two, you can reach. I think what the industry needs to do or the buyers of RPA need to take the pressure off this immediacy of the ROI. In a sense, that's what's driven the value. I can deploy something, I can get value in a few months but, to really make it effective and transformative you need to combine it with these AI components, that's going to take a little longer, so this sort of impatience that you see in a lot of companies, they should really step back and take a look at the more end to end capabilities and take a little hit on the ROI immediately so that you can do that. >> No, I mean I can definitely see a step function, okay, great, we've absorbed that value, we get the quick ROI, but there's, to your point there's got to be some patient capital to allow you to truly transform in order for RPA, I don't want to put words in your mouth, to live up to the hype. >> Absolutely, I totally agree. And I am still very, very high on the market, I think it's going to do extremely well. >> Well, if you look at the spending data, it's quite interesting. I mean RPA as a category is off the charts. You know, UiPath, from the, your last wave kind of took the lead but, Automation Anywhere, Blue Prism spending, even in traditional incumbents, maybe not even RPA, maybe more "process automation" like Pegasystems. Their spending data suggests that this is the rising tide lifting all boats so, my question to you is, how do you see this all shaking out? I mean, huge evaluations, the bankers are swarming around. You saw them in the media yesterday. You know, at some point there's got to be a winner takes most. The number two guy will do pretty well and then everybody else kind of consolidates. What's your outlook? >> Well, there are a lot of emerging players coming into the market and, part of my life is having to fend them off and talk to them, and the RPA wave is coming out in a week. It's going to have four new players in it. Companies like SAP. >> Well, they acquired a company right? >> They acquired and they built internally, and have some interesting approaches to the market. So you are going to see the big players come into the market. Others I won't mention that'll be in the market in a month It's getting a lot of attention. But also I think that there are domains, business domains that, the different platforms can start to specialize in. The majors, the UiPaths to the world, will be horizontal and remain that way. And depend on partners to tailor it for a particular application area. But you're going to see RPA companies come into the testing market, software testing market. You're going to see them come into the contact centers to deal with attended mode in more sophisticated ways perhaps than those that don't have that background. You're going to see tailored robots that are going to be in these robot communities that are springing up. That'll give a lot of juice to others to come into the market. >> And like you say you're going to see, we've talked about this as well Rebecca, the best of breed versus the suite, right? Whether its SAP, Inforce talking about it, I'm sure Oracle will throw its hat in the ring I mean, why not, right? Hey, we have that too. >> Well, if you're those companies that the RPA bots are feasting on, they're slowing the upgrades to your core platforms, in some ways making them less relevant, because their argument has been, let's integrate, you get self integration when you buy SAP, when you buy Oracle, when you buy these big platforms. Well, the bots actually make that argument less powerful because you can use the bots to give you that integration, as a layer, and so they're going to have to come up with some different stories I think if they're going to continue to move forward on their platforms, move them to the cloud and so forth. >> So, finally, your best advice for workers in this new landscape and how it is going to alter their working lives. And also, your best advice for companies and managers who are, as you said, maybe not quite, they're grappling with this issue but maybe not and they're not being disingenuous to workers about who's going to lose their jobs, but this idea of as they're coming to terms with understanding quite all of the implications of this new world. >> Yeah, I know, I'm presenting data tomorrow that shows that organizations, employees, and leaders are not ready and I have data to show that. They're not understanding it. My best advice, I love the concept of, it's not a Forrester concept, it's called constructive ambition. This is the ability in an employee to want to go a little bit out of the box, and learn, and to challenge themselves, and move into more digital to close that digital skills gap. And, we have to get better at, companies need to get better at identifying constructive ambition in people they're hiring, and also, ways to draw it out. And to walk these employees up the mountain in a way that's good for their career and good for the company. I can tell you, I'll tell a few stories on the main stage last night, I interviewed Walmart employees and machinists that could no longer deal with their machine because they had to put codes into it so they had to set it up with programming steps and the digital anxiety was such that they quit the job. So a clear lack of constructive ambition. On the other hand, a Walmart employee graduated from one of their 200 academies and was able to take on more and more responsibility. Somebody with no high school degree at all. She said, "I've never graduated "from anything in my life. "My kids have never seen me "succeed at anything, and I got this certification "from Walmart that said that I was doing this level "of standard work and that felt really, really good." So, you know, we, companies can take a different view towards this but they have to have some model of future of work of what it's going to look like so they can take a more strategic view. >> Well Craig, thank you so much for coming on theCUBE. It was a really great talk. Another plug for the book, "Invisible Robots in the Quiet of the Night" you can buy it on Amazon. >> Craig: Thank you. >> I'm Rebecca Knight for Dave Vellante, stay tuned for more of theCUBE's live coverage of UiPath Forward. (techno music)

>> From Times Square, in the heart of New York City, it's theCUBE. Covering Imagine 2018. Brought to you by, Automation Anywhere. >> Welcome back everybody, Jeff Frick here with theCUBE. We're in Manhattan, New York City, at Automation Anywhere's Imagine Conference 2018. About 1,100 professionals really talking about the future of work bots, and really how automation is gonna help people do the mundane a little bit easier, and hopefully free us all up to do stuff that's a little bit more important, a little higher value. We're excited to have our next guest, he's Craig Le Clair, the VP and Principal Analyst from Forrester, and he's been covering this space for a long time. Craig, great to see ya. >> Yeah, nice to see you, thanks for having me on. >> So, first off, just kind of general impressions of the event? Have you been to this before? It's our first time. >> Yes, I did a talk here last year, so it was a little bit smaller then. There's obviously more people here today, but it's pretty much, I think it was in Brooklyn last year. >> It was in Brooklyn, okay. >> So, this is an upgrade. >> So, RP Robotic Process Automation, more affectionately, probably termed as bots. >> Yeah. >> They're growing, we're seeing more and more time and our own interactions with companies, kind of on the customer service side. How are they changing the face of work? How are they evolving as really a way for companies to get more leverage? >> Yeah, so I'll make one clarification of your sentence, and that's, you know, bots do things on behalf of people. What we're talking to in a call center environment is a chat bot. So, they have the ability to communicate or really, I would say, attempt to communicate with people. They're not doing a very good job of it in my view. But, bots work more in the background, and they'll do things for you, right? So, you know, they're having a tremendous effect. I mean, one of the statistics I was looking at the other day, per one billion dollars of revenue, the average company had about 150 employees in finance and accounting ten years ago. Now, instead of having 120 or 130, it's already down to 70 or 80, and that's because the bots that we're talking about here can mimic that human activity for posting to a general ledger, for switching between applications, and really, move those folks on to different occupations, shall we say. >> Right, right. >> Yeah. >> Well it's funny, Jeff Immelt just gave his little keynote address, and he said, "This is the easiest money you'll find in digital transformation is implementing these types of technology." >> Yeah, it's a good point, and it was a great talk, by the way, by Jeff. But, you know, companies have been under a lot of pressure to digitally transform. >> Right. >> You know, due to really the mobile, you know, mobile peaked around 2012, and that pushed everyone into this gap that companies couldn't really deal with the consumer technology that was out there, right? So then you had the Ubers of the world and digital transformation. So, there's been a tremendous focus on digital transformation, but very little progress. >> Right. >> When we do surveys, only 11% are showing any progress at all. So, along comes this technology, Robotic Process Automation that allows you to build bots without changing any of the back end systems. There's no data integration. You know, there's no APIs involved. There's no big transformation consultants flying in. There's not even a Requirements Document because you're gonna start with recording the actual human activity at a work station. >> Right. >> So, it's been an elixir, you know, frankly for CIOs to go into their boss and say, "You know what, we're doing great, you know, I've just made this invoice process exist in a lot better way." You know, we're on our path to digital transformation. >> And it's really a different strategy, because, like you said, it's not kind of rip and replace the old infrastructure, you're not rewriting a lot of applications, you're really overlaying it, right? >> Which is one of the potential downfalls is that, you know, sometimes you need to move to that new cloud platform. You don't want, to some extent, the technology institutionalizes what could be a very bad process, one that needs to be modernized, one that needs to be blown up. You know, we're still using the airline reservation systems from 1950s, and layers, and layers, and layers and layers built upon them. At some point, you're gonna have to design a new experience with new technology, so there's some dangers with the seduction of building bots against core systems. >> Right, so the other thing that's happening is the ongoing, I love Moore's Law, it's much more about an attitude then the physics of a microprocessor, but you know, compute, and store, and networking, 5Gs just around the corner, cloud-based systems now really make that available in a much different way, and as you said, mobile experience delivers it to us. So as those continue to march on and asymptomatically approach zero and infinite scale, we're not there yet, but we're everyday getting a little bit closer. Now we're seeing AI, we're seeing machine-learning, >> Yes. >> We're seeing a new kind of class of horsepower, if you will, that just wasn't available before at the scale it's at today. So, now you throw that into the mix, these guys have been around 14 years, how does AI start to really impact things? >> It's a fascinating subject and question. I mean, we're, at Forrester, talking about the forces of automation. And, by the way, RPA is just a subset of a whole set of technologies: AI, you mentioned, and AI is a subset of automation, and there's Deep Learning, is a subset of AI and you go on and on, there are 30, 40 different automation technologies. And these will have tremendous force, both on jobs in the future, and on shifting control really to machines. So, right now, you can look at this little bubble we had of consumer technology and mobile, shifting a lot of power to the consumer, and that's been great for our convenience, but now with algorithms being developed that are gonna make more and more decisions, you could argue that the power is going to shift back to those who own the machines, and those who own the algorithms. So, there's a power shift, a control shift that we're really concerned about. There's a convergence of the physical and digital world, which is IOT and so forth, and that's going to drive new scale in companies, which are gonna further dehumanize some of our life, right? So that affects, it squeezes humans out of the process. Blockchain gets rid of intermediaries that are there to really transfer ideas and money and so forth. So, all of these forces of automation, which we think is gonna be the next big conversation in the industry, are gonna have tremendous effect societally and in business. >> Right. Well, there's certainly, you know, there's the case where you just you can't necessarily rescale a whole class of an occupation, right? The one that we're all watching for, obviously, is truck drivers, right? Employs a ton of people, autonomous vehicles are right around the corner. >> Right. >> On the other hand, there's going to be new jobs that we don't even know what they're gonna be yet, to quote all the graduating seniors, it's graduation season, most of them are going to work in jobs that don't even exist 10 years from now. >> Correct, correct, very true. >> And the other thing is every company we talk to has got tons of open reqs, and they can't get enough people to fulfill what they need, and then Mihir, I think touched on an interesting point in the keynote, where, ya know, now we're starting to see literal population growth slow down in developed countries, >> Yes. >> Like in Japan is at the leading edge, and you mentioned Europe, and I'm not sure where the US is, so it's kind of this interesting dichotomy: On one side, machines are going to take more and more of our jobs, or more and more portions of our job. On the other hand, we don't have people to do those jobs necessarily anyway, not necessarily today, but down the road, and you know, will we get to more of this nirvana-state where people are being used to do higher-value types of activities, and we can push off some of this, the crap and mundane that still, unfortunately, takes such a huge portion of our day to day world? >> Yeah, yeah. So, one thought that some of us believe at Forrester, I being one of them, is that we're at a, kind of, neutral right point now where a lot of the AI, which is really the most disruptive element we're talking about here, our PA is no autonomous learning capability, there's no AI component to our PA. But, when AI kicks in, and we've seen evidence of it as we always do first in the consumer world where it's a light version of AI in Netflix. There's no unlimited spreadsheets sitting there figuring out which one to watch, right? They're taking in data about your behavior, putting you in clusters, mapping them to correlating them, and so forth. We think that business hasn't really gotten going with AI yet, so in other words, this period that you just described, where there seems to be 200,000 people hired every month in the ADP reports, you know, and there's actually 50,000 truck driver jobs open right now. And you see help-wanted signs everywhere. >> Right, right. >> We think that's really just because business hasn't really figured out what to do with technology yet. If you project three or four years, our projections are that there will be a significant number of, particular in the cubicles that our PA attacks, a significant number of dislocation of current employment. And that's going to create this job transformation, we think, is going to be more the issue then replacement. And if you go back in history, automations have always led to transformation. >> Right. >> And I won't go through the examples because we don't have time, but there are many. And we think that's going to be the case here in that automation dividends, we call them, are going to be, are being way underestimated, that they're going to be new opportunities, and so forth. The skills mis-match is the issue that, you know, you have what RPA attacks are the 60 million that are in cubicles today in the US. And the average education there is high school. So, they're not gonna be thrown out of the cubicles and become data scientists overnight, right? So, there's going to be a massive growth in the gig economy, and there's an informal and a formal segment of that, that's going to result in people having to patch together their lives in ways they they hadn't had before, so there's gonna be some pain there. But there are also going to be some strong dividends that will result from this level of productivity that we're gonna see, again, in a few years, cause I think we're at a neutral point right now. >> Well, Amara's Law doesn't get enough credit, right? We overestimate in the short-term, and then underestimate the long-term needs affect. >> Absolutely. >> And one of the big things on AI is really moving from this, in real time, right? And all these fast databases and fast analytics, is we move from a world where we are looking in the rear view mirror and making decisions on what happened in the past to you know, getting more predictive, and then even more prescriptive. >> Yes. >> So, you know, the value unlock there is very very real, I'm never fascinated to be amazed by how much inefficiency there still is every time we go to these conferences. (Craig laughs) You know we thought we solved it all at SAP and ERP, that was clearly-- >> Clearly not the case. Funny work to do. >> But, it's even interesting, even from last year, you mentioned that there the significant delta just from year to year is pretty amazing. >> Yes, I've been amazed at the level of innovation in the core digital worker platforms, the RPA platforms, in the last year has been pretty amazing work. What we were talking about a year ago when I spoke at this conference, and what we're talking about now, the areas are different. You know, we're not talking about basic control of the applications of the desktop. We're talking about integration with text analytics. We're talking about comp combining process mining information with desktop analytics to create new visions of the process. You know, we weren't talking about any of that a year ago. We're talking about bot stores. They're out there, and downloadable robots. Again, not talking about last year at all. So, just a lot of good progress, good solid progress, and I'm very happy to be a part of it. >> And really this kind of the front end scene of so much of the development is manifested on the front end, where we used to always talk about citizen developers back in the day. You know, Fred Luddy, who was just highlighted Service Now, most innovative company. That was his, you know, vision of Citizen Developer. And then we've talked about citizen integrators, which is really an interesting concept, and now we're talking about really citizens, or analysts, having the ability via these tools to do integrations and to deliver new kind of work flows that really weren't possible before unless you were a hardcore programmer. >> Yeah, although I think that conversation is a little bit premature in this space, right? I think that most of the bot development requires programming skills today, and they're going to get more complicated in that most of the bot activities today are doing, you know, three decisions or less. Or they're looking at four or five apps that are involved, or they're doing a series of four or five hundred clicks that they're emulating. And the progression is to get the digital workers to get smarter and incorporating various AI components, so you're going to have to build, be able to deal statistically with algorithm developments, and data, and learning, and all of that. So, it's not.... The core of this, the part of it that's going to be more disruptive to business is going to be done by pretty skilled developers, and programmers, and data scientists, and statistical, you know, folks that are going through. But, having said that, you're going to have a digital workforce that's got to be managed, and you know, has to be viewed as an employee at some level to get the proper governance. So you have to know when that digital worker was born, when they were hired, who do they report to, when were they terminated, and what their performance review is. You gotta be doing performance reviews on the digital workers with the kind of dashboard analytics that we have. And that's the only way to really govern, because the distinction in this category is that you're giving these bots human credentials, and you're letting them access the most trusted application boundaries, areas, in a company. So, you better treat them like employees if you want proper governance. >> Which becomes tricky as Mihir said when you go from one bot to ten bots to ten thousand. Then the management of this becomes not insignificant. >> Right. >> So Craig, I want to give you the last word. You said, you know, big changes since last year. If we sit down a year from now, 2019, _ Oh. >> Lord knows where we'll be. What are we gonna talk about? What do you see as kind of the next, you know, 12-month progression? >> You know, I hope we don't go to Jersey after Brooklyn, New York, and-- >> Keep moving. >> I see Jersey over there, but it's where it belongs, you know, across the river. I'm from Jersey, so I can say that. You know, I think next year we're gonna see more integration of AI modules into the digital worker. I think with a lot of these explosive markets, like RPA is, there's always a bit of cooling off period, and I think you're going to see some tapering off of the growth of some of the platform companies, AA, but also their peers and compatriots. That's natural. I think that the area has been a little bit, you know, analysis and tech-industry loves change. If there's no change, there's nothing for us to write about. So, we usually over-project. Now, in this case, the 2.8 billion-dollar market project five years out that I did is being exceeded, which is rare. But I expect some tapering off in a year where there's not a ceiling hit, but that, you know, you end up with going through these more simple applications that can be robotized easily. And now you're looking at slightly more complicated scenarios that take a little more, you know, AI and analytics embedded-ness, and require a little more care, they have a little more opaque, and a little more thought, and that'll slow things down a bit. But, I still think we're on our way to a supermarket and a lot of productivity here. >> So just a little less low-hanging fruit, and you gotta step up the game a little bit. >> I guess you could, you said it much simpler then I did. >> I'm a simple guy, Craig. >> But that's why you're the expert on this panelist. >> Alright, Craig, well thanks for sharing your insight, >> Alright. >> Really appreciate it, and do look forward to talking to you next year, and we'll see if that comes true. >> Alright, appreciate it, take care now. >> He's Craig Le Clair and I'm Jeff Frick. You're watching theCUBE from Automation Anywhere Imagine 2018.

>> Narrator: Live, from Miami Beach, Florida it's theCUBE covering UiPathForward Americas. Brought to you by UiPath. >> Welcome back to Miami everybody. You're watching theCUBE, the leader in live tech coverage. I'm Dave Vellante with my cohost Stu Miniman. We got all the action going on behind us. We are seeing the ascendancy of Robotic Process Automation, software robots. one of the leader's in that industry, one of the innovators, Daniel Dines is here, he's the founder and CEO of UiPath. Hot off the keynote, Daniel, thanks for coming on theCUBE. >> Daniel: Thank you for inviting me. >> Dave: You're very welcome, so, the great setup here, the Fontainebleau in Miami's an awesome venue for a conference this size; about 1500 people. In your keynote, you talked about your vision and we want to get into that but, go back to why you started UiPath. >> Daniel: I started UiPath to have joy at work, to do what I like, and to build something big. >> Dave: And you're a Developer, right? I mean you code-- >> Daniel: I am a Software Engineer. >> Dave: I mean, I can tell by the way you're dressed. (laughter) Developer CEO. >> Daniel: Yeah. >> Dave: Yeah, okay, so but you have a vision. You talked about a robot for every person. You mentioned Bill Gates, the PC for every person. I said a chicken for every pot, Harry Truman. What is that vision? Tell us about it. >> Daniel: Well, in our old day they work, we do a lot of menial stuff, repetitive, boring stuff. It's-- that is not human-- it's not human-like. Why not having this robot that we can talk to, we can command and just do the boring stuff for us? I think it's no-brainer. >> Dave: Right. >> Daniel: We just didn't think it's possible. We showed with our technology this is possible, actually. This is an angle of automation that people didn't think it was possible before. >> Dave: Well, so I neglected to congratulate you on your early success, I mean, you said one of your tenants is you're humble. So you got a lot of work to do, we understand that. But you've raised over $400 million to date, you just had a giant raise, we had Carl Eschenbach on in our Palo Alto studios. He was-- he was one of the guys in the round. So that's confirmation that this is a big market, we've pegged it at around a billion dollars today, 10x growth by 2023, so very impressive growth potential. What's driving that growth? >> Daniel: It's all from the customers. When they see it working, it's a "wow," it's different, they won't go back to the same way of delivering work. It's changing how people really work. You see people becoming joyful when we show them the robot, and they say, "I don't need to do this stuff anymore? Wow." Imagine people doing the same reports every day, going through hundreds of page and clicking the same-- this is, this is nirvana. >> Dave: And we saw customers, UnitedHealth was on stage today, Mr. Yamamoto has a thousand robots, Wells Fargo's up there, you had some partners. So you're doing that hard integration work as well. Stu, you noted that the global presence of this company was impressing you. You're thoughts on that. >> Stu: Yeah, absolutely, I mean first of all, company started in Romania, we had-- you know you don't see too many American keynotes where there's a video up there in a foreign language. It's Japanese with English subtitles, you've got customers already starting with a global footprint. What's it like being a founder in a start-up from Europe playing in a global marketplace? >> Daniel: Well, actually it help us to become-- we've been born global. We are one of the first start-ups born global from day one. We've been this company, with Japanese talent, Indian talent, Romanian talent, American talent. And being from this remote part of Europe help us... think big, because really are-- we cannot build this start-up only with Romanians. That's clear, we don't have the pool of talent. So why not just go in global, get the best talent we can and spread global? And we are one of the few companies in the world that has their revenue split equally across the three big continents. >> Stu: Yeah, Daniel, the other thing that struck me-- you're growing the company very fast. We talked about the money, but you said you're going to have over 4,000 employees by 2019. You know, I play a lot in the open source world, it's often small-team, you've got to go marketplace, how come you need so many employees for a software company? Maybe explain a little bit that relationship with a customer, how much you, you're technical people, what they need to do to interact and help them to grow these; is it verticals, you know, what's that dynamic? >> Daniel: Well, first of all, we hire more than 1,000 people in last year alone. We started from 200 and now we are 1,400. We need all these people because this technology is at the intersection of software and services. We need to help our customers scale, and we need to inject a lot of customer success people making our customer successful. My, my way of building a company is customer first. We want to offer this boutique type of approach to our customers, and they are happy. And they-- and we build this trust relationship. This is why we need so many-- We have 2,000 customers. Next year, we have 5,000 customers. We need our people to help them grow. >> Dave: We're going to have Craig Le Clair on a little later. He's the Vice President of Forrester Research. They've done a deep dive in this marketplace in the last couple years now. UiPath has jumped from number three to number one in the Forrester wave, and when you look at that report, really, the feature and function analysis shows you guys lead in a number of places. In listening to your keynote, I discerned several things that I wonder if you could explain for our audience. It sounds like computer vision is a key linchpin to your architecture, and there seems to be an orchestrator and then maybe a studio to enable simple low code, or even no code automations to be developed. Can you describe, so a layperson-- your architecture, and why you've been able to jump into the lead. >> Daniel: Well, we've done everything wrong as a start-up. We spent like seven years building a computer vision technology that-- it was of little use, back then. We did it just because we liked it. And now, this is our powerful weapon, because, what's important for this robot is to be accurate, and to be able to work in any situations. Why our technology works better, is that we do way better the extra mile of automation. 80% of the job anyone can do, even with free software. But the last 20% is where the real issues is. And with the last 20% there is no automation. And we are doing way faster. So all our signal sources-- the fact that we've done something against Lean, against every principal in start-up, we had the lecture in building so many years technology, without even envisioning the use. But when we found the market, and it was a great product market, then we scale the company. >> Dave: There are a couple key statistics that I want to bring up and get your thoughts on. We know that there are now more jobs than there are people to fill those jobs. We also know that the productivity hasn't been increasing, so your vision is to really close that gap through RPA and automation. So your narrative is really that you're not replacing humans, you're augmenting humans, but at the same time, there's got to be some training involved. You guys are making a huge commitment in training. You're going to train a million people, that's the goal, within three years. We have Tom Clancy on next. We're going to ask him how he's going to do that. But talk about that skills gap and how you're embracing re-training. >> Daniel: Well, we realize that at some point that change management, it's kind of the key-- it's the cornerstone of delivering this technology. Because there is inertia, there is fear, and-- if we bring, at the same time, automation and training, it solves this-- that solve this issue. And we have to think big; this is why: one million is a big goal, but we will achieve it because we-- I love my way to think big. I was thinking small for so many years, and thinking big it's like, it's like liberty. You sat down and realize, "Yes, you can." >> Stu: Daniel, we talk a lot about digital transformation. The automation often doesn't get talked, but in big companies; Microsoft, Oracle, SAP, seems a natural fit, I saw some of them are your partners, you came from Microsoft, maybe talk about that dynamic about how some of the, you know, big players that, you know, have the business process applications, how your solution fits with them, you know, are they going to be paying attention to this space? >> Daniel: Well, digital transformation, it's a big initiative for everybody. And RPA, it's actually right now, recognizes the first step in digital transformation. And obviously that if was RPA, AI, big business applications, it's not one single angle, but we covered the last mile of automation. We've covered the impossible, before, before this. And our automation first view of the world is beyond digital transformation because companies will exist after they build for digital transformation. But automation first is a, is a mindset. It's rethinking your operations by applying automation first. >> Dave: You have an open mindset, which is interesting. You even said on stage that, "Look, our competitors are beginning to mimic "some of our features and functions and our approach." And you said, "That's okay." I was surprised by that, especially given your Microsoft background, which was like, grind competitors into the ground. What's changed? Why the open mindset and why do you believe that's the right approach? >> Daniel: Look at Microsoft, Microsoft has changed. This is the-- it's much better, it's-- you feel better as a human. When you can offer something, "This is up, take it, give me feedback." We've been able to build way faster than them, having our open and free community. Open the software-- It gives you more joy as a developer seeing thousands of people than just guarding my little secret just for fear someone will copy it. It's way better. >> Dave: Now, you said on stage that a lot of people laughed at you when you were starting this company, you dream big. Somebody once said, Stu, that, "If you believe you can do it, "or you don't believe you can do it, you're right." "So you got to believe," was one of the things that you said. >> Daniel: That's the first thing. >> Dave: Yeah, so share with the young people out here who are dreaming big, everybody in their early 20's, they're dreaming big. Tell us about your story, your dreams, people who laughed at you, what were they laughing about and how did you power through that? Where did you get your conviction? >> Daniel: Well, first of all, they don't dream big enough. It's very difficult to big dream enough because you have your, you know-- it's the common sense that comes into the picture and it's the fear of other people laughing at you. And we haven't dreamt big enough. For 10-- for the first 10 years, we just wanted to make a good technology, the best technology that we can but that's not big enough. Big enough is change the world, big enough is bring something that makes people life better. This is big enough. If they think making people lives better, that's big enough. Nothing else is big enough. >> Dave: Well I love the fact, Daniel, that your mission-driven; that's clear. You're having some fun. You know this-- these apps are really a lot of fun. Do you still code? >> Daniel: No but I do a lot of software design and review. >> Dave: Okay, so you help, so the coders, they-- how do-- what's that dynamic like? You have-- obviously experienced developer. Do you sort of, tell them which path to go down or which path not to go down? Do you challenge them? What's your style, as a leader? >> Daniel: I challenge them to do things faster, always. They-- I ask them, let's do this feature and they say, "Two month." "No, two days." Why not? And then we go and break that one and it's a lot of conversation but usually we will deliver. Fast-- fast is also a way of being. Fastest company wins, and fast is a-- it's not easy to change the mind. Because you want-- maybe you want to be very organized, very sophisticated. If you are fast, you have to be ready to make mistakes, reverse your decision going, but you will go fast in the end. >> Dave: So that is kind of Steve Jobs-like, set a really challenging goal, and people somehow will figure it out, but culturally, you seem friendlier, nicer. It's not grinding people anymore, it's inspiring them. Is that a fair assessment? >> Daniel: My goal is to have the happiest team employees everywhere. Hap-- I like to be happy. I started this company for the joy of doing what I like, why not, this is, this is what I want for everyone. And we are-- we recently scored in comparably as one of the best company in terms of people happiness. >> Dave: Well congratulations, thanks so much for coming on theCUBE. >> Daniel: Thank you very much for inviting me. >> Dave: Really a pleasure having you. Alright, Stu and I will be back with our next guest. Right after this short break, we're live from UiPath... in Miami, you're watching theCUBE. Stay right there. (electronic music)